Digital Marketing Archives

Customer Journey Analytics Optimizes Demand Generation Marketing

To do it successfully, you need visibility into every step of your customers’ journeys and the means to track and analyze their data to understand what motivates them now and in the future. But how do you do that? Fortunately, customer journey analytics provides valuable insights into your visitors’ behavioral patterns and preferences throughout their entire customer journey. These insights allow you to create enhanced customer experiences that motivate visitors to reach the endpoint in your sales funnel.

What exactly is customer journey analytics, and how can you use it to optimize your lead generation marketing strategies? Let’s find out.

What Is Customer Journey Analytics?

As the name suggests, customer journey analytics is an application that explicitly analyzes customer journeys. This application involves tracking and analyzing the way your customers use various channels to interact with your brand. It analyzes all channels — used currently and in the future — that your customers touch directly.

These channels could include:

Channels with human interaction, such as call centers
Two-way interaction channels, such as display advertising
Channels that are fully automated, such as mobile devices or websites
Third-party operated channels, such as independent retail stores
Channels that offer live customer assistance, such as joint site navigation or live chat

Why Do I Need Customer Journey Analytics?

Even as customers’ journeys have grown increasingly complex, today’s customers expect their business interactions with your brand — across multiple channels — to be on par with CX leaders such as Amazon and Google. If your customers’ journeys aren’t seamless every step of the way, they will become dissatisfied and quickly move on to a competitor. Conversely, studies show that positive customer experiences drive revenue growth.

Studies also show that investment in customer feedback management isn’t enough to improve your CX levels. This failure is attributed to the fact that feedback is generally only requested at points along the journey. Unfortunately, this means that only some of the customer journey is captured, misrepresenting your customers’ overall experiences.

This incomplete data reduces your ability to gain a complete picture and accurate insights into your marketing strategy performance. It also leaves you at a disadvantage for enhancing customers’ experiences and tying customer experiences to tangible business outcomes.

Customer journey analytics is the bridge between your customers’ behaviors and your business outcomes. A customer journey analytics program enables your business to track, measure and improve customer experiences across several touchpoints and time periods, encompassing the entire customer journey.

Leveraging customer journey analytics enables demand generation marketing leaders to answer complex questions, such as:

What causes our customers’ behaviors?
What past interactions or journeys have our customers undertaken that led them here?
What paths do our customers take on their journeys?
What are the most likely outcomes for each customer or journey?
How will these journeys and outcomes impact our business outcomes?
What are our customers’ goals?
How do their goals align with our business goals?
How do we add value for each customer and enhance their customer experience?

What Are the Benefits of Customer Journey Analytics?

Customer journey analytics is a vital ingredient in an effective customer journey management program. It is the piece that analyzes comprehensive data and generates actionable insights. The insights gained from this type of customer management program are valuable for both customers and businesses alike. Here’s how.

Optimized Customer Experiences

The insights gained through effective analyses of your customers’ journeys enable you to optimize each step along the way for a seamless overall experience.

Ongoing Measurable Performance Results

In addition, ongoing analytics allow you to continuously measure demand generation marketing initiatives’ performance across multiple channels and define the appropriate KPIs to measure each journey.

Data Analyses From Numerous Channels and Timeframes

When you look at customers’ journeys across several channels and timeframes, authentic pain points become evident. Identifying these pain points enables you to take action and positively impact your customers’ journeys.

How Can I Optimize Customer Journey Analytics?

Customer journey analytics is typically optimized by leaders in customer service, analytics, marketing and CX. These leaders adopt customer journey analytics platforms to improve their demand generation marketing strategies and performance measurement capabilities.

These teams optimize customer journey analytics to:

Amass customer journey data
Resolve multi-channel customer identities
Analyze innumerable interactions throughout countless cross-channel journeys
Identify CX pain points and their root causes
Verify potential customer journey enhancements
Quantify CX investments’ ROI

Customer Journey Mapping vs. Customer Journey Analytics

As a demand generation marketer, you may already implement customer journey mapping and feel that it provides the same insights as customer journey analytics. Unfortunately, this is not the case. While journey mapping focuses on qualitative insights, customer journey analytics is more quantitative and incorporates a much larger scope.

Static Snapshots vs. Continuous Detail

Journey mapping provides only static snapshots of some of your customers’ journeys and lacks the required detail to represent the multitude of your customers and their unique behaviors.

Static vs. Time-Based Data

Customer journey analytics is driven by time-based data, allowing you to see how customers’ journeys change over time. The ability to continuously measure complex multi-channel customer journeys and touchpoints along journeys help marketers predict customer journey successes.

Trial and Error vs. Real-Time Testing

Without visibility to up-to-date data on each interaction along the customer journey, businesses are left to experiment with new enhancements on the entire customer journey. Not only does this potentially waste time and resources, it means marketers will be waiting for aggregated results that don’t pinpoint where the issues are.

Customer journey analytics provides marketers with the visibility to see how customers respond to improvements along several touchpoints and time periods. In addition, this application enables marketers to test and track the success of customer experience interaction improvements in real-time.

Powered by machine learning and AI, customer journey analytics enables marketers to identify pain points along the entire customer journey that negatively impact CX. These insights allow data-driven businesses to prioritize opportunities for customer journey optimization and drive revenue growth.

By Arun Sivashankaran|2021-07-09T02:19:14-07:00July 8th, 2021|Uncategorized, Conversion Rate Optimization, Digital Marketing, Analytics, The Funnel|0 Comments

Revamp Your B2B Landing Page: 5 Things to Consider

Today, we’re going to talk about what might be the most important page on your website. No, it’s not your home page, or your contact page, or that snazzy blog post that got lots of clicks. It’s your landing page.

Landing pages are the pages that leads land on right before they convert. This is the page that should sell your product or service best. If you don’t get your landing page right, your sales are going to be undercut.

If your current landing page isn’t getting it done, then it’s time for a refresh!

5 things to consider when revamping your B2B landing page

Below are some of the most critical things to keep in mind when revamping your B2B landing page for maximum effectiveness.

1. Have a clear value proposition

First things first, you need to have a clear value proposition. As soon as your lead starts scanning the page, they should be getting an idea of what your product can do for them.

This is especially important when you’re offering an unfamiliar product or service. Everyone already knows the value of a cloud storage service, but not everyone will understand why they need NAS drives in their office at first glance.

That said, familiarity doesn’t translate to a value proposition. If you’re selling in a popular market, then your value proposition is going to be what differentiates you. If everyone already knows what Slack, Zoom, Skype, and email are, then what unique selling point do you have to offer, and what’s the fastest way to showcase it on your landing page?

2. Make sure the journey from your marketing campaign to your landing page is cohesive

Next, you need to view your B2B landing page as your user’s end point in a marketing campaign journey. From the first time someone hears about your product to the moment they’re about to make a purchase, they are on a journey with your brand.

Visuals are a great way to tie this journey together. Using colors, images, logos, and keywords throughout your marketing campaign to your landing page will help solidify the landing page’s purpose for your leads. Conversely, changing up your visual narrative and tone on the landing page can dissociate the customer’s previous experiences from your landing page, breaking the customer journey at the last moment. Essentially, it’s crucial to stay cohesive with your language, messaging, visuals and call to action.

3. Have an obvious CTA front and center, and reduce navigation elements

Another key component of a cohesive B2B landing page is a clear call to action (CTA). CTAs are proven methods of pushing engagement, despite how naggy they may seem on the surface.

Not only do they work, but they help leads make their decision, too. If someone visits your landing page and either A) Doesn’t know what the page is for, or B) Can’t find the CTA, then they’re probably going to scroll around and then click away.

Don’t let this happen to you! Whether your CTA is a “Buy Now!” button, a sign-up form, or a choice between payment plans, make sure it’s the first or second thing that your visitors see.

4. Showcase your testimonials and partnerships on your landing page

For our last two tips, we’re going to tie everything together with actionable steps. The first of which is to establish trust quickly.

In B2C, entry trust (i.e., before the customer becomes a repeat customer) comes from reviews and word of mouth. Consumers want to hear that a product is great from their peers before they hear you say it.

B2B works much the same way, except that your customers’ peers are going to be other businesses. This means you’re going to want to rely on testimonials and partnerships rather than reviews.

Having familiar logos on your landing page as well as kind words will quickly ingratiate you with your leads. If they recognize brands that you’ve partnered with or see their needs and issues reflected in your positive testimonials, they’ll trust your product before they’ve made it to the checkout page.

5. Create a video to engage with the visitor

Our second actionable tip is to place a video on your landing page. It might sound crazy, especially if you’ve never invested in video content before. But in the same way that blog content drives leads, video content drives sales. In fact, it often does it better.

A landing page video should be a concise pitch of your product, about 2-3 minutes at the most. You should quickly explain what your product does, what problem it solves, how its features solve that problem, and if you have time, include a story from someone who has had success with your product.

In case you haven’t put it together, that’s your entire landing page in one engaging pitch. Except for your CTA, which should be sitting right next to the video.

Boost your B2B landing page performance with FunnelEnvy

While the five revamping tips listed above are a great way to get started, it’s far from everything you need to craft an engaging B2B landing page. And if you don’t have a lot of experience in this area, it can be tough to know how to even implement the above suggestions.

To supplement your experience, you can partner with FunnelEnvy. In case you couldn’t tell, we’re lead-generating experts, and we have a solid grasp on how to turn your landing page into a conversion machine. We offer services like Lead Gen Experiences, which will help you turn your traffic investment into a moneymaker, and Account Match, which will identify the most high-value accounts for your business and help you target them.

Reach out to the FunnelEnvy team today and start growing your business like never before.

By Arun Sivashankaran|2021-07-12T23:53:17-07:00July 7th, 2021|Uncategorized, Conversion Rate Optimization, Digital Marketing, Testing, Experimentation|0 Comments

Revenue attribution: Everything You Need to Know to Ramp Up Your Marketing ROI

Revenue is a top priority for any business, no matter how big, no matter how small. It’s fundamental: without money coming in, you’ll have nothing to cover overheads or invest back into the company.

We all know that a hard-working sales team is key for bringing in new business and increasing revenue. But revenue is increasingly a priority for marketing teams too.

Many marketers turn to ROI (return on investment) to determine the profitability of a promotional campaign. In fact, more than 40% of marketers claim their main priority in 2021 is to “better measure the ROI of [their] demand generation initiatives”.

It makes sense: effective marketing should achieve a healthy return on investment (ROI) and generate new revenue. A portion of this can then be invested back into marketing campaigns to keep bringing in more money, and so on. It’s a cycle of profitability that can help businesses grow and grow.

And revenue attribution can help you create more effective, successful marketing campaigns. But what does it mean and involve?

In this article, we’ll explore everything you need to know about revenue attribution and how it relates to improving marketing ROI.

What is revenue attribution?

Revenue attribution (also known as marketing attribution) is a reporting process that involves matching revenue brought in, to a specific marketing output.

For example, you might utilize revenue attribution techniques to monitor the impact that a particular piece of thought leadership content made on sales within two months of its publication. Or you may prefer to track the effect that a new series of videos made on revenue over a shorter or longer period.

Businesses have more channels — and more opportunities — to reach consumers than ever with targeted marketing campaigns. But it’s unbelievably competitive and marketing teams must take advantage of real creativity to make an impact, especially in the most crowded sectors or niches.

Employing revenue attribution techniques empowers marketers to hone in on their most effective work and understand how they can keep refining their techniques over time.

Why is revenue attribution important and how can it help?

Revenue attribution is crucial for marketing teams who want to gain a clear insight into their strategies’ value and learn how they affect customer engagement. Fortunately, there’s a wealth of data available online to help marketers build an accurate overview of campaign performance and ROI.

Identifying how specific campaigns and strategies have been received by audiences (target and/or general) enables you to make more informed, calculated decisions on future campaigns.

You’ll have a tighter grasp on what works, what doesn’t, and what elements should be combined to cultivate the most impactful marketing campaigns. You’ll be able to capture more leads, close more sales, and improve ROI thanks to continued analysis.

Another key benefit is that revenue attribution helps businesses (particularly those in their infancy or experiencing financial challenges) get more out of their marketing spends while still streamlining their budget.

Essentially, it can make your money go further. You’re not throwing ideas at the wall to see what sticks — you’re basing your decisions on provable facts.

You can jettison those marketing techniques and campaigns that fail to bring in satisfactory ROI. All resources usually dedicated to those will be put to better use on more effective options instead.

How can you use a revenue attribution model to measure and ramp up your marketing ROI?

We understand what revenue attribution is and why it matters. But how do you put a revenue attribution model to work and start improving your marketing ROI?

While it can appear complicated for newcomers, and more than a little daunting, it will seem far simpler when we take a deeper look. In this section, we’ll cover how to use this model to both track and measure ROI — and improve it.

What types of revenue and marketing attribution models are available?

First-touch attribution

The first-touch (or first-click) attribution is one of two single-source models (along with last-touch attribution, below).

In this model, the first channel with which a converted user engages receives all credit for generating revenue. This could be an in-depth whitepaper, a blog post, a video, or any other piece of marketing content that captures the lead’s interest enough to drive a conversion.

For example, around half of marketers describe webinars as the top-of-the-funnel format generating the most high-quality leads.

While a spectacular piece of content can be enough to push users towards a sale, the first-touch model may have a blindspot — a failure to take other interactions following this first one into consideration.

As a result, you may not have an accurate insight into how effective other channels are in swaying users’ decisions.

Last-touch attribution

Last-touch (or last-click) attribution is regarded as another easy model. Why? Because it involves looking at the final touchpoint before the sale is completed, which is usually simple to find.

The last touch could be something as straightforward as a well-researched sales call or a webinar that whets the lead’s appetite and inspires them to commit to a purchase.

However, the last-touch attribution model may overlook previous interactions with a user. These could include a visit to your website or hearing an ad for your business on a podcast. And, again, this could cause you to overlook the value of other channels

Multi-source attribution

As you can probably assume, the multi-source (or multi-touch) attribution model focuses on all channels that lead to a conversion. Multiple touchpoints will be attributed instead of just one.

Still, while the multi-source attribution model is more of a holistic approach to measuring marketing success, there’s a crucial factor to consider: it doesn’t provide an accurate reflection of a specific touchpoint’s actual contribution to a conversion. It could lead to a false representation of certain channels’ role in the customer journey.

Six multi-source attribution models are available:

Linear: This is the easier model to implement, providing all touchpoints with the same weight, though it can be hard to determine which were most important (as mentioned above).
Time decay: Touchpoints will be separated by bigger and bigger gaps in long sales cycles. With the time decay model, you’ll apply greater credit to those in the later stages than those in the earlier period. They might not have been as valuable to the eventual outcome, and in particularly long sales cycles, the buyer might have totally forgotten about their initial interactions with your business anyway.
U-shaped: A U-shaped revenue attribution model applies the credit to two main touchpoints, with fixed percentages. These are the initial touchpoint and the last, as well as any between those points. The first and last touchpoint receive 40% of the credit each. The 20% remaining is split between those touchpoints taking place in between.
W-shaped: A W-shaped model is similar to the one above, but it adds an extra touchpoint: when a prospect is converted into a lead. So, this covers the first touchpoint, the last touchpoint, and the occurrence falling somewhere between them. These receive 30% of the credit each, while the remaining 10% is shared among other touchpoints that may be detected between them.
Full path: The majority of the credit is assigned to the key steps in the customer journey and the rest goes to those touchpoints between. Unlike the other models explored so far, this includes follow-up chats between the customer and the sales team.
Custom: Teams can come up with their own weighting shares according to the channels used, customer behaviors, etc. For example, you may decide that a user who subscribed to your newsletter should have more weight than someone who clicked on an ad.

Weighted multi-source attribution

Weighted multi-source attribution involves accounting for every interaction during the sales cycle and assigning weight to the most important touchpoints. This model can lead to the most reliable views of a customer’s journey.

However, it’s one of the most challenging to put into effect, as weight must be applied to a potentially large number of touchpoints.

Why is it so important for marketing and sales teams to work in partnership?

Traditionally, businesses tend to keep sales and marketing activities separate. They consider marketing teams’ role to create leads and sales teams’ to transform them into paying customers. That’s simple enough to understand — but it could be a big mistake.

Why?

Because overhauling and refining your marketing to achieve an increase in leads won’t guarantee a rise in high-quality leads.

Yes, marketing teams can drive clicks and interest, but a large proportion of leads could be of a lower quality than expected.

The aim should be to bring in leads more likely to evolve into conversions, based on carefully targeted marketing with specific demographics in mind.

By uniting your marketing and sales teams, you can start to develop a clearer understanding of which marketing efforts bring in the most valuable leads and, ultimately, conversions. Those that consistently generate the weakest leads and harm ROI should be replaced.

What are the key benefits of using these revenue and marketing attribution models?

Here are five key benefits of using revenue and marketing attribution models:

Improved ROI
Effective revenue attribution provides businesses with an accurate insight into how much return they gain on their marketing investments. Over time, you can start to cultivate a better awareness of those techniques and strategies that engage your target audience best.

And you’ll keep reaching the right people with the most appealing messaging. This will increase the number of conversions you can expect to achieve and, eventually, the ROI you earn.

Save money on ineffective marketing
Attribution models reveal the most important touchpoints throughout sales cycles and show how marketing money is best invested. Fewer funds will be wasted on dead-end marketing.

That may free up money to channel into better marketing or other areas of your business, including sales or post-purchase support.

Hone your audience targeting
Audience targeting is one of the top methods through which advertisers increase demand. And studying attribution data reveals which types of content, messaging, and channels engage your ideal customers best.

Marketing teams can keep sharpening their material to consistently engage your target demographic(s) and minimize the risk of missteps.

Learn how to make products or services better
Marketers can get a better understanding of target customers through attribution data analysis.

Over time, this can open your eyes to ways in which you can improve products or services to suit your audience better. For example, the response to a blog post covering specific software features could inspire future releases.

The power of Revenue Funnel Optimization

Hopefully, you’re now in a place where you can see the key benefits of revenue and marketing attribution to your business. But, one of the most important aspects of attribution strategy is acting on attribution insights. And, that’s where we come in…

We’ve designed our Revenue Funnel Optimization strategy so you can get the most out of your revenue insights.

FunnelEnvy enables you to generate revenue insights by updating analytics to measure the complete end-to-end customer journey. You can pinpoint the most valuable funnels, offers, and other factors that drive revenue.

Revenue funnels comprise strategy sets focused on maximizing your website’s revenue generation through targeting the most effective offers to the priority buyer segments in your top conversion funnels.

Funnels can also be personalized by the user’s stage in the customer journey to maximize revenue further. You also can run campaigns and experiments on your most important funnels. Use direct response best practices to optimize offers, messaging, and more.

With Revenue Funnel Optimization, your decisions are driven by data and genuine insights into the buyer journey.

You’ll make stronger choices for your marketing and sales teams — and your business as a whole — by studying the facts.

Many companies are already achieving success with Revenue Funnel Optimization, with up to 250% growth in revenue and a 10x increase in Marketing Qualified Leads (MQLs).

Want to try Revenue Funnel Optimization? Start using FunnelEnvy and drive real revenue growth for your business!

By Arun Sivashankaran|2021-06-04T00:02:29-07:00June 2nd, 2021|Uncategorized, Conversion Rate Optimization, Digital Marketing, The Funnel, Strategy, B2B|Comments Off

Multi-Step Interactive Forms Advanced Use Cases(ABM/Personalization)

Hey everyone. My name is James Niehaus, and today I’m going to walk through some advanced use cases for multi-step interactive forms. Specifically, where it can help you with ABM and personalization on your website. And this is actually part two to an initial video I did around introducing everyone to interactive forms, why we love them so much, why they’re pretty effective for our clients, and how you can get started with them as well. So this is kind of part two of that series. All right, let’s jump right into it.

So we’ll cover here the following things.

A quick recap on multi-step interactive forms
Why they work
Why they are ideal for your ABM and Personalization programs
5 ways multi-step forms can enhance your ABM and Personalization programs

All we’re doing here is taking your longer static forms on your website, breaking them up into steps, making them interactive, and leading with intent questions that get them to raise their hand and express who they are and what they want to do. So this has converted really well for our clients. As you see here, these are some examples of actual lifts we’ve seen with form conversions on forms that get started and talk to sales and get demos.

Full Recap of Multi-Step Interactive Forms

Before we jump into those, just a quick recap of why we think it works well, and what some best practices are.

So always lead within 10 questions if possible. So what’s in it for them, who they are, what they’re looking for. As opposed to starting with, “What’s your first and last name, your email, or your phone number?” Right? We want to make it easy for them to get started and engage. Secondly, we want to ask a couple of those 10 questions initially, before we show them the rest of the form, because we wanted them to, one, commit, get some easy answers out of the way, and get momentum towards completing their task. So we found that this is definitely a sweet spot to kind of maximize conversions on a multi-step experience. And then lastly, just really set proper expectations. How many steps are involved, and what happens after you submit the form? Just so they right context about time and what’s going to happen next. All makes sense hopefully? Good.

Examples of Multi-Step Form Flows

multistep form examples

Some best practices of multi-step interactive forms

Results we’ve seen from multi-step interactive forms

multi step form results

So let’s jump right into why multi-step forms are ideal for targeting and segmentation. Hopefully, it’s pretty obvious, but in these experiences, and in those first couple of questions where we ask for either profile or intent questions, we’re getting valuable information that they want to share to better customize their experience or get better information from us. So we want to use that information to provide, one, them a better experience, but also ideally personalize based on who they are and their company. So that’s what ABM and personalization are all about. Personalizing based on who they are and the company they’re from. Based on what you know about them and based on what you hopefully want to achieve with them in partnership.

1. Use their answers to assign them to a segment

Use their answers to better assign them segments for analytics and campaigns. That seems pretty obvious. More importantly, use those answers to personalize the rest of that form experience. So as they provide you information about them, provide feedback that you can support their needs, you can provide specific information about their product interest. But use that moment to actually provide reinforcement for what they’re looking for. Also, you can actually potentially use that information to route them to a different funnel or experience. So the whole idea is that not everyone should be treated the same. Your higher value prospects may be given a shortcut to talk with sales. Maybe the less valuable users may be given more of a self-service route. But use their answers and their profile to route them in the most appropriate place to maximize your limited resources, but also provide them the more appropriate experience.

What’s even more compelling and potentially more exciting is the idea that we actually change the experiences based on who they are and what company they’re from. Now, rather than simply have one form for everyone, the idea here is that we take their answers or their inputs, and based on our business strategy we may serve them a different next step. So an example on the right, you see here based on the email and company domain, based on whether that matches a target account or not, they either can skip the form and go right to the scheduler. Or if they’re maybe not our targeted account, they would get a regular traditional form.

Here are some examples of getting their answers and then assigning them to a segment

2. Use their answers to personalize the rest of the form

Customize the remaining questions, messaging, and visuals to reinforce the benefits of their selection. By using these answers to personalize the rest of the actual form experience. So if they express certain product interest or indicate they’re from a smaller enterprise, you want to reinforce that you are the right business for them, that here are the benefits of that product, or maybe here are the reasons why you’re great for SMB or enterprise, or for this industry, or for this type of role, technical or maybe marketing focused.

You see an example, a very simple example where, on a contact us form, we just simply asked for their product interest in step one, and we then personalize the rest of the form based on that answer. So this is where you can use that information at the moment to reinforce the benefits of your business, your offering, your expertise, in a way that’s going to reinforce based on who they are and what their intent is. We’ve done this with a couple of clients and we’ve seen pretty nice positive upticks in conversion rates from this simple concept.

3. Use their answers to route them to a different funnel

If you identify a top target you can:

Skip form
Shorten form
Change questions
Trigger Drift/Chat

4. Target and personalize in future sessions/other channels

We can target and personalize not just at that moment, but also in future sessions, in other channels. We don’t have to stop at the form. So that’s by the information we know about them, use it wherever and whenever you see them again. And then lastly, target. Over time you actually can create different questions based on their profile. So if you have certain key segments that come to your site, you can potentially target them ahead of time and actually serve them with a different actual form experience. A little more advanced, but again, as you’re committing to this strategy, you’ll see more and more ways to use it to your advantage.

5. Target intent questions based on their profile

The idea here is, don’t let go of the information after they complete that form. What you want to do is repeat that message, reinforced that information, and follow up interactions, whether it be a session to the site, whether it be another channel like email or display, retargeting perhaps. But the whole idea here is you’re getting valuable information at the moment from an engaged user. Use it for your advantage. Okay. So that would mean if they express certain product interests. When they come back, maybe that homepage here will change to show that product, sort of that category affinity type technique. Or based on their role, reinforce the use cases for their role. Or based on their industry, show again, case studies for their industry, for their size, or any other ideas. An example on the right you see here, where we’re targeting the homepage here all based on their different stages they’re in that we identify in the process.

And then lastly, the idea here is … and over time, as you refine the strategy, this will become its own strategy. So much as you have with, say, your Marketo email programs, you have different nurture sequences. Or in Drift, you may have different Drift playbooks. The idea here is, over time, you recognize that you have certain key target accounts, segments, and ICPs that you’ll want to route through different form experiences. So rather than having one interactive form for everyone, you may eventually end up where you have different forms for your top segments and groups. So I don’t recommend doing this day one, but as you evolve the strategy, actually see what works, what doesn’t work, you’re going to see natural segments that perform better, or might need more guidance or handholding. This is where the strategy, once it starts getting those double-digit improvements, these are natural ways to further enhance and refine the program. And again, this is going to only make your personalization and ABM programs more targeted, because you’re targeting based on those same attributes that you care about and you want to personalize for.

So the quick takeaways here.

Multi-step forms. great conversion tactic. And we recommend you do this on your site today. But we think it works even better, as you’ve hopefully seen here when you combine it with your ABM personalization strategies.

5 ways to get started:

Segment by their answers they provide you
Customize a form based on those answers for a better conversion rate and better experiences.
Route them by their answers
Target them in return sessions/other channels by their answers
As you get more advanced and more mature in this strategy, start building different forms for your top use cases and your top segments.

Learn More on Multi-Step Experiences

Go to our website, funnelenvy.com/blog, and you’ll be able to check out the content and hopefully enjoy this and other content that’s similar. And with that said, thank you for your time. If you have questions, just drop me an email. And if you want to see our own interactive quiz, you can hit our website. And that quiz will actually help you evaluate whether you’re the right fit for working with us. So check it out and hopefully we can talk soon. With that, take care.

By James Niehaus|2021-08-31T03:19:25-07:00April 28th, 2021|Uncategorized, Conversion Rate Optimization, Digital Marketing, The Funnel, B2B|0 Comments

How Marketing Teams Should Optimize Website for Conversions that Align with B2B Sales

You might have heard before that marketing and sales can sometimes experience the business version of a sibling rivalry, but it’s not quite what you think.

Within business-to-business (B2B) organizations, marketing’s focus is on generating leads, while sales focuses on getting those leads to close. A disconnect happens when your marketing team (with good intentions) focuses on volume over quality, therefore resulting in passing over a high volume of leads to sales that just won’t close.

In this article, we’ll walk through a framework for how to categorize leads that come in through your website, how to build website messaging and landing pages that are consistent and relevant for each type of category, and how to optimize for intent as you go.

A General Framework for Categorizing Website Leads

It might seem obvious that your marketing team should focus on quality over quantity, or ideally both at the same time, but in practice the two can get a bit muddled.

We recommend generally categorizing leads into three different buckets:

High volume, high intent. These leads should be sent to sales and prioritized.
High quality, Low intent. These leads should be sent to a nurture funnel where they continue to be educated and engaged.
Low quality. These should get filtered out altogether, or directed to a different offer.

Ultimately, we’re talking about being more efficient with qualification by allowing your website to do a lot of the work for you.

This includes building consistent messaging for each lead category, building and presenting relevant landing pages for those people, and optimizing for intent as you go.

Create Messaging that’s Consistent and Relevant

In order to qualify each website visitor as a member of one of the lead categories above, you’ll need to be able to automatically consider two things before displaying website content:

How that person got to your website. The messaging on the page they visit should be consistent with the email, ad, social posts, blog post content, or search result that preceded it.
Their business demographic. Use marketing automation, CRM and / or 3rd party data to ensure that messaging is also relevant to their business size or industry. Focus on the industries and business sizes that have an expected value for your sales teams, and send all others into the low quality bucket.

One effective way to do so is to display case studies from relevant industry competitors, if you have them available.

For example, if someone from Wells Fargo visits your fintech website, they’ll likely respond more positively to a landing page with logos or success stories from Chase or Bank of America then from Investopedia or Stripe. If that’s not in the cards for you, focus on business size first. Before showing a Wells Fargo visitor logos from a fintech startup, show a success story from Macy’s, Delta, or another enterprise business.

This example from Shopify that’s optimized to attract businesses in e-commerce fashion. The logos and success stories listed on the page include e-commerce fashion brands, like AdoreMe, Cee Cee’s Closet and Coco and Breezy, immediately signaling to other fashion e-commerce companies that Shopify’s solution might be a good fit for them.

This example from Shopify that’s optimized to attract businesses in e-commerce fashion.

FunnelEnvy offers reverse IP, or account matching, and real time data integration to help marketers surface insights that allow them to display industry-specific webpages like these.

We also help companies display pages based on other types of data, like funnel stage, company size, and more.

This example from a large call center showcases how experimenting with personalized offers on their website by buyer segment led to an increase in qualified leads.

In fact, MQLs increased by 10X between March and June of 2020.

Graph showing MQLs increased by 10X

Landing pages that set the right expectations

Your landing pages essentially start the sales process by presenting your products to people for the first time. For them to be effective, they need to accomplish two things:

Mimic your sales people. This should be true for every lead category. Once a person converts through your website and makes it to the stage where they speak to sales, they shouldn’t receive an entirely different message than what led them to convert in the first place.
Clearly communicate what each site visitor should expect next. This will change depending on the lead category. If your site visitor is categorized as “high quality, high intent” and on their way to talking to a sales person, tell them that. If they’re getting redirected to a different offer or getting more information sent to their inbox, tell them that instead.

One common mistake we see companies make is sending leads to a discovery meeting with a sales development representative (SDR) after they register for a demo. They’re expecting to see the product, when in fact, they end up in a frustrating meeting where they’re asked a lot of questions, afterwards which the real demo is scheduled depending on how they’ve qualified.

One way to rectify this is to make the discovery process part of the inbound flow, like we do at FunnelEnvy.

Our quick questionnaire helps us to categorize site visitors that convert so that we can set expectations for what will happen next, once they’ve completed the form.

Take a moment to fill out this questionnaire

Here’s another example that qualifies leads using company size and sales strategy:

Example that qualifies leads using company size and sales strategy

Optimizing for intent as you go

You’ve created messaging for each lead category and set up your landing pages so that the right expectations are set. Now it’s time to take it a step further by putting in place a mechanism to filter out low-quality leads or show them a different offer.

If a website visitor that’s not a highly valuable lead for your sales team comes along, you’ll want to be able to identify them with data that reveals their business size, industry, title, or any other identifying signal that makes a difference for you.

If someone comes along that doesn’t fall into any of the buckets you’ve identified as high value, consider sending them to your self-service solution (if one exists) or including a message upfront that right now, you’re just not the right fit for one another.

While it might seem scary to direct some leads away from sales, it can actually improve your sales team’s productivity and have a positive impact on revenue.

Working with FunnelEnvy, one startup increased their monthly marketing qualified leads (MQLs) by 30%, and grew revenue from closed or won deals by 250% the following quarter. Here’s what that success looks look over time:

One startup increased their monthly marketing qualified leads (MQLs) by 30%

This success came from optimizing their website to align with their B2B sales strategy, and by only surfacing high quality leads to their sales teams that were ready to buy.

Bonus: treat your high quality leads like gold

Those leads that are high quality and have the appropriate purchase intent should be treated like gold.

To ensure that your sales team is successful, make sure there’s an established service-level agreement (SLA) on when and how sales is following up on those leads. For example, Marketo’s sales team commits to a 24-hour SLA.

If a tight 24-hour turnaround isn’t in the cards for you, automate your follow-up process with marketing automation or your customer resource management (CRM) software.

End the infamous sibling rivalry

The infamous sibling rivalry amongst marketing and sales isn’t actually a sibling rivalry at all — in fact, it only exists when these teams try to help one another in the wrong way.

Your website can do most of the heavy lifting to close this gap and help to qualify leads that are sent to sales automatically.

If you’re looking for a custom solution to help personalize your website content for leads of different types, FunnelEnvy can help — contact us.

By Megan Morreale|2021-04-19T15:40:48-07:00April 15th, 2021|Uncategorized, Conversion Rate Optimization, Digital Marketing, Analytics, B2B, Experimentation|0 Comments

Solving the Revenue Funnel Data Challenge

Transcript:

Hi, everyone. I’m Arun from FunnelEnvy. Today I want to spend some time talking about how we solve the revenue funnel data challenge.

Of course, many of you are running multiple campaigns on lots of different channels. You have digital advertising, paid acquisition campaigns that are heavily optimized, and you spent a lot of time getting people into your marketing automation platform and running really personalized email nurture campaigns to them.

Now, of course, the main problem that we focus on at FunnelEnvy is that the main thing in the middle that glues a lot of that customer journey together is your website. Of course, for many of us, it’s a static experience. Unlike the other channels, prospects and customers keep coming back to that same static website. In many cases, it’s just not keeping up and dragging down your conversion rates and ultimately your pipeline that you’re delivering to the sales team.

Now, that’s a broad example of some very specific demand gen website problems that we commonly run into. You’re probably looking at website analytics, and if you’ve spent any time in there, it’s not easy to tell which experiences and offers, things like landing pages or other offers, content, are actually contributing to revenue. Maybe you’re running experiments and campaigns on your website, and it’s also hard to measure the pipeline and revenue impact from those website experiments. Of course, a static website that’s showing the same thing to every buyer at every stage isn’t very effective at moving prospects efficiently through the funnel.

Now, of course, the demand gen revenue journey is long and complex. This is just one example of someone coming to the site, downloading content, getting on an email sequence, attending a webinar, talking to sales who finally opens it up and later on closes the deal. The important thing to understand is that, of course, that revenue journey occurs in multiple different contexts, multiple different channels, and ultimately different platforms in our backend martech stack, from the website and the website analytics to the marketing automation platform and ultimately the sales team and the CRM platform.

Now, the net effect of this is we end up creating a lot of data silos in our stack. Website analytics, the CMS or the optimization tools, maybe third-party firmographic data providers, our backend systems like marketing automation and CRM, these are all silos of information that all have individual pieces of that entire customer journey. We can think of those individual pieces as pieces of the puzzle that, if we put together, can actually present a cohesive picture of those individuals and accounts and their opportunities as they move throughout that customer journey.

Now, the important thing is having that glue that can bring all of those puzzle pieces together and not only receive data from those individual systems, but also feed them and also feed our business intelligence or reporting. For now, we’re going to call that a customer data platform, or CDP. This is similar to a data warehouse, but it has some very specific features that we want to see to be able to solve some of those problems that we were talking about.

First off, it’s not just sufficient for this CDP to receive data. It needs to have bi-directional integration to a lot of these solutions so it can pass data between these different platforms. Certainly, it unifies all of these puzzle pieces, or that profile data, and because we’re talking about demand gen, it happens both at an individual and an account level. It has that full view of the customer journey, so unlike website analytics that’s only looking at what’s happening on site, it has that perspective tied to that unified customer profile of what happens not only on the website, but also down the funnel as that leads to account progress towards revenue. It allows for rich segmentation because we have those unified customer profiles and full perspective on that buyer journey, and because we’re talking about website optimization, allows for real-time resolution to be able to target those different audiences on the website.

Let’s get into some of the specific use cases of the customer data platform. First off, we can use it to enhance our existing web analytics. If you spend a lot of time looking at your website performance and in platforms like Google Analytics you know that you’re typically only looking at those vanity metrics, things like bounce rates and visits and exit rates. Unfortunately, a lot of the interesting data that we have lives in our marketing automation, our CRM, the leads, contacts, accounts, and opportunities that we’re really seeking to improve and understand.

By pumping this data into our CDP and unifying it and then feeding those down-funnel outcomes into our web analytics, as well as our reporting and dashboards, we get a much more complete picture of that revenue journey for that visitor. This lets us answer questions like which experiences and offers on my site are actually contributing to revenue, and how much? You see here a landing page report, but instead of only looking at your typical vanity metrics you see on the right, we actually can visualize the closed one revenue of each of those landing pages. Of course, you can take any of those dimensions that you’re typically looking at in a web analytics and understand the pipeline and revenue impact this way.

You can also answer ad hoc questions through dashboards, like my website traffic, not just in terms of numbers, but by different buyer stages and the expected revenue of each. This often starts the hypothesis process of how can I actually target those different buyer stages differently to accelerate them through that revenue funnel.

Once you actually get into running experiments and campaigns, it can be very difficult to understand how much pipeline and revenue those experiments and campaigns are actually generating, especially if you’re using a multi-touch attribution model, which many of you are. We can solve that problem by bringing, again, that lead, contact, account, and opportunity data, as well as the touchpoints in my attribution model and the test and campaigns from the optimization platform, and feeding those into my reporting and business intelligence environment.

By doing that, we can start looking at the amount of sourced pipeline using that attribution model that my website campaigns and experiments have delivered over time. We can start comparing campaigns, not just on their ability to get people to fill out a form, but based on the actual pipeline and revenue impact that they’ve had. We can look at individual campaigns and the variations in those campaigns and understand which variation is most effective, again, not just in terms of those onsite vanity metrics, but their ability to deliver results down the funnel.

Finally, when we’re talking about optimizing the revenue funnel, a lot of it is about targeting in real time and targeting the right offers to different personas, different groups of accounts, and my personal favorite, by buyer stage, to move prospects more efficiently through the funnel. Now, to do this, again, we’re bringing over that same marketing automation and CRM data, but potentially also that website behavior from web analytics, and in this case, feeding that into audiences in our content management system or our testing and optimization platform. In this case, this isn’t a reporting use case, so that audience has to be delivered in real time based on an individual visitor as they come into the site. If you can do that though, we can start doing things like personalizing those offers based on that buyer stage and where they are in the journey, or even differentiating offers and changing the experience in real time to present the best offer based on the persona that’s coming to the site.

With that, I want to leave you with some takeaways. If you’re a demand gen marketer and you’re looking at your website performance and even optimization of it, our recommendation is always not to settle for top-of-the-funnel KPIs. Those vanity metrics, those engagement metrics, even form conversions, they’re not sufficient. Really, you should be trying to align your efforts with the way the rest of the team and organization measure success. For a demand gen team, that’s based on pipeline and revenue impact.

Of course, demand gen sites, demand gen marketers, typically deal with long customer journeys. What that often means for your site is that you have a lot of return visitors. They’re coming back to the site at different stages in the buying journey with differentiated intent, but the measurement of pipeline and revenue and the ability to understand those different buyer stages and ultimately target them is really related to how efficiently you can bring that data together and activate it in real time.

Then finally, many of you may have already invested in a data lake or data warehouse to unify that data that you have in these different silos together. Typically, this is done for attribution use cases and other reporting and measurement use cases. It’s a great starting point. Our CDP often compliments existing data lakes or data warehouses, but the reason that we have to compliment it is that typically those are solutions that aren’t built for that real-time use case. If you get into the targeting and activation of that data in the milliseconds that are required by the time a visitor comes to the site and you deliver them that web experience, it requires a real-time source, in our case, the FunnelEnvy customer data platform.

With that, I want to thank you for listening today. Bye.

By Arun Sivashankaran|2021-06-18T05:48:19-07:00March 10th, 2021|Uncategorized, Conversion Rate Optimization, Digital Marketing, B2B|0 Comments

Don’t Fear a Cookieless World, Instead Shore Up Your First-Party Data to Optimize Your Funnel

If you haven’t yet heard, the cookie is on the outs — much to the cookie monster’s chagrin. The death nell was sounded by Google’s announcement of Privacy Sandbox, which is basically their plan to create a set of privacy standards.

This plan includes improving how cookies are classified, clearing up the details behind each person’s cookie settings, and plans to aggressively block fingerprinting. A fingerprint is created by stitching together a bunch of tiny signals about a person to create a full profile, and since people can’t access or delete their fingerprint, Google’s basically going to make it impossible to create them.

All of these intentions add up to one pretty plausible result — third-party cookies (the type used to make fingerprints, and fuel activities like retargeting) won’t be around much longer.

There’s another type of cookie though that’s not going anywhere — the first-party cookie, which allows marketers to collect first-party data. Focusing on shoring up your first-party data will not only prepare you for the death of the third-party cookie, but result in a stronger marketing strategy overall, regardless of the third-party cookie’s fate.

In this article, we’ll talk about the difference between the first and third-party cookie, why the first-party data is more valuable anyway, and how to use it to optimize your demand generation funnel.

First-party cookies vs. third-party cookies

Before we get into exactly how and why you should focus on first-party data, let’s straighten out the two types of cookies:

A first-party cookie is created and stored by the website you’re visiting; the one in the address bar. If you’re a site owner, first-party cookies allow you to collect data like customer analytics, language settings, the user journey, and other information that can assist you in improving your customer experience on-site.
A third-party cookie is created by sites other than the one you’re currently visiting. These other sites own some of the content, like ads or images, that you see on the site you’re currently visiting, and can therefore collect information about you while you’re there.

For example, say you’re shoe shopping with popular retailer DSW. When you visit DSW.com and shop for boots, you might not purchase right away. During that first visit, the homepage looks like this:

The next time you visit their site, there’s a new section of the homepage that displays the shoes you clicked on during your last visit. DSW dropped a first-party cookie on their site in order to remember that you were interested in buying boots. They then used this information to personalize your experience the next time you visited their site.

During this second visit, you made a purchase and provided your email. Two days later, DSW sends you an email about an upcoming boot sale. That’s first-party data. DSW used a combination of first-party cookies and personally identifiable information (PII), namely your email address, in order to personalize your experience.

Third-party cookies are most often used to retarget you on sites other than DSW.com. Perhaps after shopping for boots, you head over to nytimes.com to read up on the news. As you’re reading an article, you see a Google-owned banner ad advertising the shoes you just looked at:

A lot of data exchange went on behind the scenes for you to see this ad. First, DSW partnered with Google and started using Google Ad Manager to serve ads around the web. The New York Times also partnered with Google to display ads on their site, in order to monetize their content.

Google then dropped a third-party cookie on DSW’s site to collect data on your visit, and DSW retargeted you on nytimes.com in the hopes of capturing your attention, and bringing you back to your site.

These are the types of cookies that Google is looking to guard against, and they’re the ones that are likely to die in the coming year.

Your first-party is data more valuable than third-party data anyway

The thought that third-party cookies are on the way out has caused a bit of a panic among marketers, mostly because they’ll have to come up with new ways to retarget site visitors.

But the thing is, focusing on first-party data is way more lucrative than scaling retargeting campaigns based on third-party data. First off, you collected that data directly from a person, and you know it’s accurate. Second, because you collected that data while that person was visiting your site, you know they’re actually interested.

Let’s go back to our shoe example — which interaction with a potential consumer would you find more valuable — the one on your owned website, or the display ad impression they probably didn’t see?

We bet your answer is the former.

First-party data is more valuable because it’s the best indicator of buyer stage, and therefore intent. Someone visiting your website has a much higher intent to interact with your brand than that of someone who saw a display ad.

For demand generation marketers, buyers go through many stages in their journey, so it’s really important that the data you’re collecting on those buyers captures their intent at each stage.

FunnelEnvy combines first-party data insights and offers personalization in order to align the offers on your website to the intent the buyer has at the time they’re visiting. This way, you move them down the funnel every time they visit, leading to better conversion rates and ultimately more revenue.

Here’s an example from Fitch Solutions. They guide their clients in making clear-sighted decisions through data, research and analytics on the capital markets and the macroeconomic environment.

Like many B2B technology companies, they thought of their homepage as a type of welcome center where they introduced themselves to people getting to know them for the first time:

But, also like many B2B technology companies, they saw a lot of returning traffic, which is often a result of having a longer buyer journey. A “welcome center” isn’t an optimal experience for someone you’ve already welcomed.

FunnelEnvy worked with Fitch Solutions to personalize their homepage experience for each visit, and for returning visitors, they surfaced a relevant offer in place of their welcome message:

This change resulted in a 55% increase in conversion on site. By doubling down on optimizing their website using first-party data, Fitch Solutions made a huge impact on their funnel.

Optimizing the demand gen funnel with first-party data

So, how do you get from collecting first party data to activating it with a personalized experience on-site? The biggest challenge for the demand generation marketer facing the death of the third-party cookie is that first-party data is often siloed away in places like your customer resource management (CRM) software, marketing automation and in website analytics.

If you want to truly personalize an experience, you need to bring all of that data together for a holistic view of the consumer journey.

The effort is well worth it — in fact, 77% of B2B sales and marketing professionals believe that personalization builds better customer relationships.

But to get there, something needs to bring all of that siloed data together so that you can target accordingly by buyer stage. The FunnelEnvy Backstage platform brings together these data sources, website analytics and experience tools to create a unified customer profile.

If you have the data, you can get sophisticated with offer personalization. You can attribute different user experiences to revenue, target by buyer stage and scale revenue.

Here’s an example from TIBCO Jaspersoft. They had one static product page that contained multiple offers for different personas within the organization.

When they tried to squeeze multiple offers on a single page, offers competed for attention and blended in, which put the onus on the user to determine which was right for them.

We worked with them to target specific personas with a single offer, based on data they had stored in their marketing automation platform. Through testing variations that replaced the default experience with a single focused offer, we saw an almost 50% improvement in revenue per visitor.

Conclusion: the death of the cookie is nothing to lament

While the death of the third-party cookie will mean a shift in strategy, there is a huge silver lining — as it’s phased out, demand gen marketers can use the opportunity to shore up their first-party data strategies, which are likely to result in a much larger impact on their funnel.

We’ll see less focus on (admittedly crappy) ad buys and retargeting campaigns, and a larger focus on leveraging first-party data insights better at home.

If you’re stuck on where to start when it comes to shoring up your first-party data strategy, we can help. Apply now to get started.

By Megan Morreale|2021-03-02T11:52:02-08:00March 2nd, 2021|Uncategorized, Conversion Rate Optimization, Digital Marketing, Strategy|0 Comments

The Secret to Making Your ABM Personalization Campaign a Success

For all the demand generation leaders out there, I’ll bet you’ve engrossed your partners, sales directors and higher level leadership team on the subject of account based marketing personalization. But be honest, do you really know what a successful outcome looks like?

visual screenshots of abm personalized accounts

ABM-based personalized campaigns are the targeted, personalized experiences that either speak one-to-one to an account, or to a group of important accounts. Per a definition found online,

“Personalized campaigns that are designed to engage each account based on the marketing message on the specific attributes and needs of that account.”

In following this logic, you’ve decided that certain accounts are more important than others, and therefore are worth the effort of this level of personalization. Great! Typically, demand generation marketers follow these steps:

Identify targeted accounts
Target those accounts in real time with personalized campaigns
Measure the effects of those campaigns

Steps one and two are pretty straightforward, and certainly there are potential pitfalls, but step number three is critical. The truth is the wrong measurement strategy could doom your ABM personalization efforts to failure.

pyramid-three-steps-abm-personalization

Choosing the Right ABM Measurement Strategy

A common way to evaluate the effect of an onsite experience is through an A/B test. This is the traditional conversion rate optimization (CRO) approach. You might run a randomized A/B test, evaluate the effect of personalizing your homepage against a baseline or control, and measure an on-site goal, like lead conversions. You can carry out this type of testing in a variety of platforms, measure the effect on your goals, and try to determine the overall impact on your personalization efforts.

homepage-optimizely-cro-website-optimization

It’s important to note however, that this approach makes several assumptions. First, it requires a large sample size to establish confidence based on statistical significance. It also assumes that all of these conversions are the same.

If you’re only looking at the difference between lead conversion for the baseline and lead conversion for the personalized option, then you’re assuming the conversions carry the same weight, measuring impact based on the quantity of those conversions, but not necessarily the quality. We should ask ourselves, are these assumptions consistent and compatible with our ABM strategy?

When we think about ABM, the fundamental goal is to capture more revenue from a smaller number of accounts. That’s how you can justify the investment in targeted ads, website personalization, or direct mail.

graphs-target-image

Keep in mind that the further up the ABM pyramid you climb, the smaller the number of accounts that can potentially drive value or expected revenue. In many cases, those white glove accounts could be worth a hundred times more value than an SMB account. Since those accounts are likely larger enterprises, they’re also likely to take longer to close.

What to Include when Measuring your ABM Personalization Campaign

Your ABM personalization strategy should include a quality metric, which includes pipeline and revenue, considered over a longer period of time.

Now this can conflict with the CRO approach that we mentioned earlier. This approach, however is very transactional, top-of-funnel, and assumes that each conversion is the same.

You may consider or are actively engaging in the traditional CRO approach to pass variation information back from your optimization platform to CRM for analysis against pipeline and revenue. Often times, this means embedding those variations that users saw in a hidden field on a lead capture form, and then building a custom report in your CRM data on the backend.

simple attribution solution

Will this get you better insight into the down-funnel impact from your personalization experiences, like pipeline and revenue? It may, but you could also wind up with a one-off solution for the website experience that doesn’t align with the way the rest of your demand gen team measures and attributes revenue.

The Right Attribution Model for ABM Personalization

You may be running a multi-touch attribution model, either with an off-the-shelf tool like Visible, or a custom solution.

These work well for longer journeys by allocating revenue back to customer journey touchpoints, like the first touch, lead creation or opportunity created, granting credit to the triggers that influenced the conversion.

bizible full attribution model path

Image Source: What is a “Full Path” Marketing Attribution Model? (Bizible | Link)

B2B attribution solutions are inherently account-based and they’re typically used for channel and campaign analysis, but they can also be used to measure the effect of on-site activities like ABM personalization campaigns.

Now, the real advantage here is by integrating your website experiences with your multi-touch attribution model. You’re aligning your website activities to the measurement strategy used by the broader demand generation team. So how does this work?

Let’s say you have touchpoints established, and you’re allocating revenue in some proportion across each one. Here, the actual percentages don’t actually matter as long as you’re are allocating revenue back to new customer touchpoints.

abm personalization touch points

Once you know the revenue at a certain touch point over a period of time, with attribution, you’ll be able to assign credit back to the activities that influenced that touchpoint conversion. As I mentioned earlier, it’s typically done at a channel and ad campaign-level, but there’s no reason that an onsite experience can’t be an influence over a touchpoint as well.

Campaigns and variations are a couple of example of onsite influences, but you could also consider chatbots, content, and anything that influenced a touchpoint. Eventually, you’ll see pipeline and revenue credit associated with the influencing on-site experiences of those touch points.

The Better the ABM Attribution, the Better Your Metrics

Rather than report on percentages like conversion lift on a superficial vanity metric, you can report on campaigns over time with respect to their sourced pipeline. These insights grant you a better understanding of the impact your on-site campaigns have on your business.

graph of results over time

Additionally, you’ll see the impact your campaigns have not only in terms of onsite metrics, but based on sourced, influenced pipeline and revenue, and closed deals.

personalization by intent chart

Variations within your experiments will give you the view you need to report on uplift based on whether pipeline or revenue correlated directly with your attribution model.

testing variation chart funnelenvy

Let’s talk about other ways you can ensure your ABM personalization efforts are a success. Start your revenue insights journey by measuring your revenue contribution of existing offers. By aligning this with your attribution strategy, you’ll gain deeper insight into your on-site offers and assess their revenue contributions.

Don’t Forget About Segmentation

Segmentation is a big part of account-based personalization. The audiences that you create will have differentiated intent. You wouldn’t want to spend time creating audience segments that are effectively the same and trigger the same experiences.

Think about how your account clusters and account groups are differentiated, and what offers they’re going to want to see that are specific to their interests within their own groups of accounts.

Now let’s pivot to the must-avoids. This includes what we call “vanity personalization,” where you add the name of a customer or account coming to the site. Instead, focus on the offers you’re putting in front of your visitor.

The ideal is to present a more relevant offer throughout the demand generation funnel to your visitor. When segmenting, think about the offers presented to these target accounts, and focus on how to increase their relevancy.

Remember, this isn’t just a top-of-funnel activity. Obviously we’re talking about demand gen marketing in this post, but consider your full customer journey as a long revenue funnel.

Once you enable yourself with the capability to personalize your ABM campaigns, think how your business can better align offer and optimize, not only for your top-of-funnel, but for each stage of your buyer journey.

By Arun Sivashankaran|2021-06-18T05:47:31-07:00February 18th, 2021|Uncategorized, Conversion Rate Optimization, Digital Marketing, B2B|0 Comments

Optimize your Revenue Funnel by Focusing on the Offers

Let’s take a step inside the data-driven demand generation marketing team. The biggest concerns on the CMOs radar are that the acquisition costs are too high and not hitting their pipeline or revenue goals. Now looking at the data, we know that not only are they spending a lot on paid and organic traffic, but the quality of the traffic is good, and it’s not converting.

So, of course, the next question would be – what can they do about it? A common answer is to focus on website conversion rate optimization, which involves running online experiments. That’s something you can put a budget around and prioritize but recognize that your executives are going to want to see impact based on pipeline and revenue and probably want to see it fast.

Online Experimentation

Back in 2017, the Harvard business review published an important article digging into the power of online experimentation. In it, they correlated successful business outcomes to a culture of experimentation.

Image Source: The Surprising Power of Online Experiments (Harvard Business Review | Link)

The article cited examples like the one below from Bing, who tested multiple different colors on their site, ran experiments. and realized an incremental $10 million in annual revenue from these experiments.

Image Source: The Surprising Power of Online Experiments (Harvard Business Review | Link)

Similarly, Google ran a test with 40 different shades of blue on their site. When they ran those experiments, they achieved $200 million in incremental revenue. Given these results, should we, as demand gen marketers, be running the same experiments?

In our opinion and experience, no, you should not.

You’re not Google or Bing. Leaving aside traffic considerations, you’re trying to influence B2B buyer behavior over customer journeys. And the reality is that groups of buyers that consider enterprise solutions are not going to buy based on the button color or other small cosmetic changes.

This is important because experimentation comes with a cost. Not only do you have people and the technology costs of running online experiments, but also your organizational ability to make decisions. So, focus on the elements that would deliver revenue and influence those B2B buyers when you’re thinking about experimentation.

When we think about the B2B buying journey or the revenue funnel it’s common to conceptualize it as a series of buyer stages. As prospects progress through those stages, they do so through exchanges, in which you’re offering something to that prospect in exchange for something else. The offer could be some content in exchange for their attention, an event, or an opportunity to speak to the sales team in exchange for their contact information. Ultimately those offers are how they learn more about your solution and how it would benefit them.

From our experience and the testing that we’ve done, the highest leverage use of experimentation for the demand gen org is to improve the relevance of those offers and the ease of engaging with them throughout the buying journey. Of course, we always want to ensure we measure the impact of those experiments based on the KPIs that matter – pipeline and revenue.

Optimizing Offers

What does it mean to optimize offers? There are three components to an effective offer. One, of course, is the offer itself. That item you’re proposing to exchange with that visitor or prospect for them to understand your solution. The more relevant it is, the more effective your ability to convert them will be.

The second important aspect is how you frame it. Our primary focus here is the headline and Call to Action (CTA). Your headline is important because a visitor will spend five or ten seconds deciding if they want to stay on your site or hit the back button and go somewhere else. So, entice them to continue reading the content on the page.

Finally, the third element of the offer is the exchange and how they provide what you want. Most likely on your site this is a web form, but it doesn’t need to be. It’s increasingly common to see conversational marketing tools (chatbots) that accomplish the same thing by providing that medium of exchange for the offer.

Examples

Let’s look at some examples of how you could optimize your offers.

Landing pages are a great starting point for thinking about your offers. Many of you are probably running traffic to dedicated landing pages and putting an offer in front of the visitors hitting it. But not every visitor is interested in the same offer. In the example below, we recognized when working with a customer that they had three viable offers for those visitors coming through their paid campaigns. And rather than only showing them one, we use data to dynamically personalize the offer itself as well as framing and the page layout to reflect what might be most relevant to that visitor.

When we ran the experiment against the static landing page we saw a 44% improvement in revenue per visitor.

For most of us the most trafficked page on our site is the homepage. And on your homepage the “above the fold” section at the top gets most of the attention. Many of us think about our homepage in the context of welcoming the first time visitor and introducing your solution as in the example below.

For SaaS and Demand Generation websites it’s common to have a lot of returning traffic. Since return visitors are familiar with your solution, it wouldn’t make sense to show them that same offer. In an experiment, we targeted these return visitors and the solutions they showed interest in and presented them on the homepage. In this case, those offers were buried in the site and require additional navigation. By presenting this offer they would likely be interested in and serving those directly on the homepage, we saw almost 55% improvement in conversions coming through this page.

You can also target well-defined buyer stages. In the following example, we have a customer with a freemium model where visitors on the free plan come to the homepage and see a CTA or a button prompting them to “Upgrade Your Plan”. The baseline experience was to take them to a set of SaaS plan tiers where they could select the one that they would upgrade to.

Using this data, we can identify the specific plans most relevant for any individual and offer them directly on the homepage. The framing included the benefits and replaced the CTA with the cost of that specific plan we recommend. Since we recommend a single upgrade plan, we bypassed the plan selection (and the friction it created) and took them directly to the credit card to upgrade. By removing friction and presenting them with a more relevant offer, we saw an almost 70% improvement in revenue per visitor coming through this experience.

The most common mechanism of exchange for the offer is the web form, and as a result, we spent a lot of time optimizing them. It’s important to recognize that there’s a lot of friction for the visitor when they encounter one of these forms.Even if they’re interested in the offer, they face the prospect of handing over their email and other personal information, which often presents a big hurdle. Since it’s common to see drop-offs at this stage, we would like to take those contact forms and reinforce the benefit and the value to the visitor filling them out. In the following example, we tested an updated version of the form page resulting in an 85% improvement in conversions.

If you have the data, you can get sophisticated with offer personalization. It’s common to see pages like the one below. It is a product page that contains multiple offers for different personas within the organization. Unfortunately, when you try to put them all on a single page, they compete for attention and blend in, making it hard for users to know which one is relevant for them.

In this case, we target specific personas visiting the page based on data we had in the marketing automation platform and identify the most relevant offer. By testing variations that replace the default experience with a single focused offer, we see an almost 50% improvement in revenue per visitor.

Final Thoughts

It’s possible to waste time, effort, and money optimizing inconsequential elements of your website. For demand generation marketers, the highest leverage things to focus on are the offers – specifically their relevance to the visitor and the ease of engaging with them.

Before you undertake this experimentation it’s important to make sure you have solid revenue insights. What that means is, evaluating your existing offers as well as future experiments based on their pipeline and revenue contribution.

Some of the personalized examples above require some segmentation. Our recommendation is to prioritize segmentation based on the differentiated intent and addressable size of those segments. We often find that marketers are running building audiences that can only address 5-10% of their audience, or ones that don’t have meaningfully different intent from one another. Ultimately those aren’t going to have much value when it comes to optimizing offers.

This is why we start with buyer stages as our starting point for segmentation because it a large set of well-understood segments with differentiated intent – buyers at different stages will naturally gravitate towards different offers. The vast majority of the visitors coming to a demand gen site fit into anonymous, known lead, active opportunity or existing customer.

Finally, when it comes to improving offers, start with common sense ideas. If you start thinking about your buyer stages, some opportunities should become apparent. For example, should a known lead see a lead capture form, or can we repurpose those pixels for something more relevant? Similarly, should existing customers see the “Request a Demo” or “Talk to Sales” CTA? Maybe there’s an opportunity to get them to support resources or event upsell them.

What’s stopping you from generating more revenue by improving offers on your website? If you’re a Demand Gen marketer and need help, feel free to get in touch.

By Arun Sivashankaran|2021-02-18T11:31:20-08:00February 17th, 2021|Conversion Rate Optimization, Digital Marketing, Analytics, Strategy, SaaS, B2B|0 Comments

We Know Why Your Online Ads Aren’t Scaling Revenue (And How to Fix It)

When you put too much pressure on something, it cracks.

Online advertising is no exception. The cracks in this ecosystem have turned into gaping holes, and those holes are why your paid ads aren’t scaling.

Three of the big ones are often in the headlines: the death of the third-party cookie, attribution as an almost impossible feat, and data privacy which is getting clearer, but still murky at best.

Yet, most of us put up with it. 84% of B2B marketers use paid distribution channels (read: Instagram, LinkedIn, Facebook, YouTube, etc.), which would be one thing if the value of those channels was clear, but a staggering 47% of us admit that we can’t measure ROI and 18% aren’t sure if they can or not.

Despite these shortcomings, when we need to scale, our first thought is often growing the budget for online ads, but will that really move the needle?

In this article, we’ll break down why your ads aren’t scaling revenue by analyzing their actual contribution to your sales funnel, calculating what would really happen if you had your dream budget, and how to fix the gaping hole in your funnel that paid channels leave unfulfilled.

What do Paid Ads Actually Contribute?

Pretty much everyone buys ads from Facebook and Google, but it’s also quite common for B2B marketers to buy ads from LinkedIn. The rest of the web is fragmented and even harder to navigate than these channels, so for the sake of argument, let’s focus on those three.

Search ads are effective, but have incredibly narrow margins, and quickly get costly if you’re not paying attention.
Facebook ads have better margins, but only if you can keep up with inevitable creative fatigue on behalf of your audience.
LinkedIn ads have the best margins of all, but they’re incredibly expensive, with an average cost of $5.26 a click versus Facebook’s $1.72.

So, they do work, but the margins are small and the cost is high. Because of this reality, most marketers make incremental investments focused on driving traffic to web pages.

We took a look at website traffic from two of our high-growth clients, and saw that those expensive investments were a drop in the bucket in comparison with organic channels.

Direct and organic traffic made up 70% to 75% of all traffic, whereas traffic from a whopping five to six paid channels only made up 25% to 35%.

In these two examples, paid search specifically accounted for 13% and 9% respectively.

But what if that 13% of traffic is where all of the revenue came from? Even in that unlikely scenario, we can’t expect it to continue to grow if this marketing team tried to scale their paid search buys.

This analysis from Search Engine Land shows that on average, after hitting a certain inflection point, your margins get smaller and smaller. This is true for all marketing channels, and is also known as The Law of Shitty ClickThroughs.

Image Source: Paid Search Portfolios: The Good, The Bad & The Ugly (Search Engine Land | Link)

This is not to say that paid advertisements don’t have a place in your marketing mix, but that alone, they won’t scale revenue profitable or quickly.

Optimizing the entire journey, which requires analyzing all channels as a whole, is the only way to scale revenue optimally. And since website traffic comes from all channels and your website is where buyers at every stage of the funnel engage, you can only do that if your web analytics are measuring revenue instead of top of the funnel vanity metrics.

How do You Scale Website Traffic so that it Ends in Revenue?

Instead of narrowly focusing on incrementally increasing website traffic with paid ads, the answer to revenue at scale lies with focusing on improving website conversions across all channels and at every stage of the buyer journey.

The chart below is a snapshot traffic analysis spanning one quarter, from a FunnelEnvy customer. This B2B SaaS company currently sees a 5% conversion rate from paid channels, which is higher than their direct and organic channels — at 2.5% and 3% respectively.

It might therefore seem logical to focus on scaling their paid channels. Let’s see what happens when they give it a shot.

This B2B SaaS company’s marketing team tested spending 50% more on paid advertising one quarter, resulting in an additional 1,000 leads. When they instead focused on optimizing their website funnel across all channels, they saw an additional 1,755 leads, a 10% improvement over just scaling paid ads alone.

As we’ve seen, online ads are subject to the same laws of diminishing returns as any other channel. So, actually achieving 10% growth from your website (which accrues to all acquisition channels), is likely to be much easier than generating 50% or more growth from your paid channels.

Optimizing your website doesn’t have to be an exclusively lead generation focused activity. In fact, you’re likely to get much better results if you can optimize all the way down funnel to pipeline and revenue. To illustrate the impact, let’s compare what happens when you optimize your top of funnel (TOFU) conversion rate with bottom of the funnel (BOFU) metrics like opportunities and closed deals.

The following FunnelEnvy customer is a B2B SaaS company in the fintech space, looking to increase the number of closed deals per quarter and reduce their customer acquisition cost (CAC).

They average about 600,000 visits per quarter and spent about $450,000 across all paid channels. When they increased their lead generation focused conversion rate alone by 30%, they saw a corresponding increase in deals closed, and a 23% reduction in CAC. However when they extended conversion improvements all the way down the funnel they saw an even greater increase in closed deals (50%), and a larger (33%) reduction in CAC.

This “Revenue Funnel Optimization” requires you to identify visitors at different buying stages on your website, and to target them with more relevant offers and experiences.

This table captures the impact of optimizing through various stages of the funnel — leads (TOFU), pipeline (opportunity creation) and closed or won deals (revenue):

An Easier, More Scalable Path to Growth Exists Across All Channels, Not with Paid Ads

The bottom line — simply increasing your spend on paid channels is not the answer to scale, and there’s a lot more growth to be found if you take into consideration how other channels impact your funnel.

As the paid advertising ecosystem racks up more and more problems and gets increasingly expensive, this is a great time to focus on elevating the value from other channels that impact your funnel.

If you’re not quite sure where to start, you’re not alone. 68% of B2B companies haven’t even identified their sales funnel. FunnelEnvy’s solution helps you close the gap between website analytics and revenue and target buyers at each stage of their journey.

If you’re a demand gen marketer that needs to scale growth efficiently learn more about our solution for Revenue Funnel Optimization.

By Arun Sivashankaran|2021-02-11T09:56:50-08:00February 11th, 2021|Uncategorized, Conversion Rate Optimization, Digital Marketing, B2B|0 Comments

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