Revenue Funnel Optimization Archives

Common Sense Personalization Examples

The MuleSoft example

Let’s look at an example of some common sense personalization ideas. We will use MuleSoft.com, a B2B provider of multiple software products, as an example.

First a disclaimer. MuleSoft is not a FunnelEnvy customer and I have no insider knowledge of their business or marketing. What I’m suggesting below are insights based on what I can determine from their website, with a healthy dose of assumptions included.

MuleSoft’s featured product, Anypoint Platform™, seems to follow a relatively standard SaaS buyer journey which includes a free trial. We can use this to put some definition around the activities that define our STDC intent clusters:

Cluster	Behavioral Criteria
See	New visitor coming to the site with no prior engagement history
Think	Visitor actively engaging with solution specific content
Do	Submitted free trial form or ask an expert form
Care	Paying customer who is having success

We can learn a lot from the technologies that MuleSoft is using on their site. They have Demandbase and Engagio, so it’s safe to say that Account Based Marketing (ABM) is a strategic priority. Since they’ve adopted ABM it’s also very likely that they have defined account tiers grouped by potential value to the business.

The navigation bar gives us clues about some of the other Account based attributes that they care about. Under the Solutions menu they list resources by initiative, integration, technology, and industry.

Digging around in MuleSoft’s training offerings helps us identify the individual roles within the accounts that they can market to as well.

With this information we can put together a contextual framework to evaluate MuleSoft’s website experience. As you can see there are a lot of variables to consider!

Rather than UX improvements or content suggestions, we’d like to personalize the entire experience – messaging, value propositions, and next best action based on an individual visitor context. Let’s look at how we might improve MuleSoft’s web experience with some of this context in mind.

The “See” Cluster

The home page is often one of the most highly trafficked pages, usually with a high volume of direct and organic (branded) search traffic. As a result, it generally has pretty generic top of the funnel content and often serves as a “traffic cop” – funnelling visitors to the sections of the site with more specific content.

What if instead of the headline, copy and CTA we could replace it with something that better reflected the visitor’s intent?

Visitor intent: Explore Government IT solutions

Visitor intent: Understand Salesforce integration possibilities

Visitor intent: Accelerate ecommerce integration

Visitor intent: Try Anypoint Platform

The three content boxes below the home page CTA could similarly be personalized based on intent. MuleSoft also has an extensive resource collection of case studies, ebooks, whitepapers and webinars. The featured content at the top of the page is prime real estate to showcase personalized content.

Accomplishing the “See” cluster

A common question that we get is how do we actually know enough about “anonymous” visitors (ones who haven’t filled out a form) to be able to personalize for them?

We’re looking for signals that could inform the right experience, and it turns out there are more than you might think. Think about how users get to the website. If you’re running ads you’re probably already segmenting based on intent and other relevant characteristics. It’s now become common for marketers to personalize landing pages, but keep in mind that visitors that hit your landing pages might browse to other areas of the site or return in subsequent sessions.

As an example MuleSoft is running search ads. Many of them provide clear signal as to the intent of the visitor who clicks through. These can be used to personalize not only the home page, but also the home page, content pages, and to take them deeper in the content journey.

Using data from incoming clicks doesn’t have to be limited to ads. Referring sites can be great indicators of customer context as well.

An article that links to MuleSoft.com. Visitors that come it are likely to be interested in MuleSoft’s Microservices offerings.

Organic search result that links to a specific MuleSoft content page. In this case the combination of referrer (Google) and landing page is a signal of customer interest.

There are third party data providers that can provide information on anonymous visitors as well. These include Demandbase (firmographic data from reverse IP lookup) and Bombora (B2B intent). If you have the budget these can also be incorporated into a model to inform personalized experiences. Even if you don’t have one of these data providers the underlying input (e.g. IP address) can be used as signal in a predictive model.

The “Think” Cluster

The requirement to be in the Think cluster is that the visitor is in the target market and has shown some commercial intent. In B2B that often means that they’ve returned to the site and engaged with more commercially oriented content, and likely filled out a gated content form. That could also mean that multiple visitors have come to the site from the same account.

We want to continue to provide these visitors with relevant content that continues to engage them, but also give them on-ramps to take the next step. In MuleSoft’s case, this “next best action” is either starting the free trial or talking to sales. Since we may also have information about the visitor’s account and role we can incorporate that into the experience and call to action. For example, we may want developers to start the trial, but IT managers at large accounts to talk to sales.

Changing the copy and CTA for a developer (end user) to encourage them to start the free trial.

If the visitor is an engaged decision maker we can present them with more specific content and a CTA that takes them directly to a Contact Sales form.

Accomplishing the “Think” cluster

As we’ve seen with behavioral data, the content that visitor engages with on site could be a strong indicator of customer intent. If a visitor has shown repeat engagement with content, and specifically engagement with content that indicates some commercial intent, they are likely to be in the “Think” cluster.

MuleSoft has a relatively large content library, and some it can be indicative of a higher intent to purchase.

A “thought leadership” ebook (left) vs an analyst report with vendor comparisons (right). The analyst report likely demonstrates higher commercial intent.

Remember that we don’t have to manually identify and evaluate each piece of content for commercial intent. We’re just looking for the machine to identify and correlate signals to outcomes. All we have to do is throw is therefore throw all of the content URLs into our model and evaluate which experiences actually convert.

Another rich set of data for the Think cluster is in our 1st party data platforms, specifically marketing automation and CRM. Most marketing automation platforms cookie every visitor which can be used to connect a website visitor to a lead record. The accounts in your CRM database can also be associated with visitors though it requires an extra step – at FunnelEnvy we usually make that connection using the marketing automation cookie or via the inferred domain from a reverse IP provider.

Website behavior as well as lead and account attributes evaluated against conversion outcomes can provide solid evidence that a customer is in the Think cluster.

The “Do” Cluster

Visitors in the “Do” cluster have shown strong commercial intent. This goes beyond filling out a form for a piece of content, they’ve demonstrated an interest in engaging in the sales process. Traditionally this is where marketing would have taken a “hands off” approach (it’s a sales problem now!) but that’s no longer sufficient.

For MuleSoft we’ve defined strong commercial intent as having submitted a Contact Us (sales) form or started the free trial. In the time between this conversion and a deal closing, the focus is often on continuing to educate the prospect, expand the champions in the account and alleviate concerns about value and cost. Effectively engaging customers in this cluster should result in higher deal velocity and overall conversion rate from qualified lead to revenue.

For a product like MuleSoft, the prospect will likely be asking certain questions depending on their role:

What support options are available relative to what I need?
What have effective implementations at similar companies looked like?
How much and what kind of training will our developers require?
What professional services or partner resources are available for implementation?

MuleSoft’s website has quite a bit of relevant content that can be both personalized and highlighted for these types of questions. All of the context that we’ve established up to this point can and should be used as well, including initiative, vertical and job function.

MuleSoft support plans can be personalized by highlight the recommended support plan and providing additional details based on the account.

MuleSoft has an opportunity to showcase partners based on what they know about the account and the specific opportunity being discussed.

Highlight training opportunities based on visitor role and surface them on higher traffic pages of the site.

Another relevant content option for customers who are considering purchasing Mulesoft might be to personalize the resources in the nav bar or replace the explainer video on the home page with recommended content related to these topics.

For prospects who have started a free trial one of the most effective strategies is to get them to engage and successfully complete certain tasks. In app engagement generally has a strong correlation to retention and in this case conversion to a paid plan. This seems to be true in MuleSoft’s case as they have a robust onboarding tutorial when a first time user logs into the trial.

Marketers often put a lot of effort into establishing intent before sign up but that doesn’t always carry over into the experience post conversion. If, for example, the visitor was interested in Salesforce integration the onboarding process could direct them towards relevant functionality once they were in the app.

Obviously not everyone is going to complete the onboarding and many will exit the app before completing a desired action. When these visitors come back to the site they could prompt visitors to sign back in and complete it.

Accomplishing the “Do” Cluster

In our example, visitors in the “Do” cluster have either filled out a contact sales form or started a free trial. These signals can be established behaviorally, but most likely you would integrate marketing automation, CRM or application data to the experience to incorporate a richer set of attributes.

For some of the examples in this cluster, an audience based approach combined with predictions can work well. A predictive model is going to show suboptimal experiences to some visitors, as in an A/B test that’s actually feature because you’re trying to explore and learn what correlates to conversion.

Sometimes you will want to restrict the range of possible “guesses” made by the predictive model, especially in the case where certain experiences clearly wouldn’t be applicable or there’s some other hard business constraint.

In situations where you have “hard constraints”, such as if a customer is in the free trial, the inherent error rate of the a purely predictive model may not be appropriate. In this case you could setup an audience for free trial users and then run a predictive decisioning model within that audience.

The “Care” Cluster

Customers in the “Care” cluster are your most loyal advocates. In SaaS solutions, not only are they paying for the solution but they’re also having demonstrable success with it. Visitors in this cluster are prime candidates for expansion and referrals, but may also need more advanced services and support.

As an organization pursuing Account-Based Marketing and Sales, MuleSoft has an opportunity to provide more value for and penetrate more deeply into their Care cluster accounts. When visitors in this cluster come to their website they could present a completely different homepage experience.

Salesforce changes the homepage experience between new visitors (left) and existing customers (right)

MuleSoft has several opportunities to deliver more value to existing customers through a personalized homepage experience. This could be in the form of:

Features that the customer are being underutilized and the customer could get more value out of.
Promoting services or partners that might be able to help the customer.
Highlighting training and certification options relevant to the visitor’s role.
Building the community by promoting location specific events.

KPIs that are relevant to the care cluster include engagement, expansions, renewals and referrals. Some of these may not be owned by the marketing team, but they’re certainly relevant to the company.

Accomplishing the “Care” Cluster

Once a customer is in the Care cluster you generally have a lot more first party data about them. This can include CRM data, but potentially also application behavior, customer support history, and success metrics. You’re trying to inform your decisions with a more holistic view of the customer, their interactions with your company and solution.

In Conclusion

If you’re struggling to understand why the same lead form and marketing automation nurture you’ve had on your website for years are not working as well as they once did take a step back because the rules of the game might have shifted underneath you.

We can’t assume the same uniformity of customer intent that we once could – and that has significant implications for experiences that we deliver across channels and particularly on the website. To deliver better outcomes it actually helps to go back to Marketing 101 – right message, right person, right time and identify the solutions and processes that will help us get there at scale.

By James Niehaus|2025-05-12T04:36:47-07:00May 11th, 2025|Revenue Funnel Optimization, Conversion Rate Optimization|0 Comments

What is PLG Routing?

PLG routing refers to the strategy of guiding users through a tailored journey based on product-led growth (PLG) principles. Instead of relying solely on traditional sales processes, PLG routing dynamically adjusts the user experience in real-time to enhance engagement and conversion opportunities. This approach ensures that users are always presented with the most relevant content and offers, optimizing the chances for success.

How PLG Routing Works

PLG routing leverages data from user interactions and behavior to determine the next best action, whether it’s directing users to specific features, offering personalized messaging, or adjusting the funnel stages accordingly. This allows businesses to create more fluid, responsive, and relevant user experiences that are guided by the individual needs and actions of each user.

The Impact of PLG Routing on Conversion Rates

By implementing PLG routing, companies can enhance their conversion strategies by continuously adapting to the user’s journey. This helps ensure that users are not overwhelmed with irrelevant content and are instead guided to the most impactful touchpoints, boosting engagement and conversion rates.

Why PLG Routing Matters for SaaS Businesses

For SaaS businesses, PLG routing is a game-changer in terms of user acquisition and retention. By focusing on personalized, product-centric interactions, businesses can effectively drive growth without the traditional heavy reliance on sales teams. This is especially important in the SaaS model, where a smooth, self-guided user journey can significantly impact long-term retention and customer satisfaction.

Watch the Full Video on PLG Routing

To gain a deeper understanding of how PLG routing can help your business grow, watch the video below where we explore the concept in more detail.

Conclusion

PLG routing is transforming how businesses approach user engagement, making it an essential strategy for any product-led company. By leveraging data-driven insights and dynamically guiding users along their journey, businesses can drive better results, improve conversions, and build stronger relationships with customers. Implementing this approach may be the key to optimizing your conversion rates and scaling your business effectively.

By David Janczyn|2025-05-12T04:37:20-07:00January 12th, 2025|Revenue Funnel Optimization, Full-Funnel Optimization, Conversion Rate Optimization|0 Comments

Improving Martech Observability to Reduce Costs and Boost Efficiency

In the world of marketing technology (Martech), analytics observability is often overlooked. Yet, without it, businesses risk inefficiencies, revenue losses, and operational setbacks. Martech observability focuses on maintaining a robust analytics infrastructure, ensuring data flows seamlessly and accurately. Let’s explore the costs of broken analytics and how improved observability can be the solution.

The Cost of Broken Analytics

Broken analytics systems are more than just an inconvenience—they are a financial burden. Without proper observability, businesses face a range of problems, including:

Revenue Loss: Incorrect or missing data results in missed opportunities and lost leads.
Operational Inefficiencies: Teams waste time and resources troubleshooting issues instead of focusing on strategic objectives.
Poor Decision-Making: Misaligned sales and marketing efforts stem from inaccurate data, leading to ineffective campaigns.
Brand Damage: Faulty campaigns delivered to the wrong audience can harm customer trust and retention.

The long-term cost of maintaining broken analytics systems often exceeds the initial cost of building them.

Why Observability Matters in Martech

Observability, a concept rooted in software development, has yet to gain widespread traction in the analytics world. However, it is the key to ensuring data reliability and system resilience. By incorporating observability practices, businesses can proactively identify and resolve issues before they escalate.

Key Strategies for Martech Observability

To strengthen your analytics infrastructure, consider two primary approaches to observability:

1. Synthetic Testing
Synthetic testing involves running scripted transactions and workflows through your systems to simulate user interactions. This proactive measure helps you spot inconsistencies or errors in data processing before they impact real users.

2. Real User Monitoring
Real user monitoring (RUM) captures real-time data from actual users navigating your systems. This method ensures data flows correctly, providing immediate insights into potential issues affecting your audience.

The Benefits of a Resilient Analytics Infrastructure

Implementing these observability practices provides numerous benefits, including:

Accurate Data Insights: Gain confidence in your analytics for smarter business decisions.
Operational Efficiency: Reduce troubleshooting costs and improve team productivity.
Stronger Brand Trust: Avoid damaging campaigns and maintain customer loyalty.
Informed Resource Allocation: Spend less time fixing data issues and more on growth-focused initiatives.

Final Thoughts: Observability as a Martech Imperative

Improving Martech observability is no longer optional—it’s essential for any business relying on data-driven decision-making. By integrating synthetic testing and real user monitoring into your analytics stack, you can ensure accuracy, prevent costly mistakes, and create a competitive edge.

Watch the video above for a deeper dive into these strategies, and start building a resilient analytics system today.

FAQs

What is Martech observability?
Martech observability is the practice of monitoring and maintaining the health of marketing analytics systems to ensure accurate and efficient data processing.

Why is broken analytics costly?
Broken analytics lead to revenue loss, operational inefficiencies, poor decision-making, and damaged customer trust, all of which negatively impact business growth.

What is synthetic testing in analytics?
Synthetic testing simulates user interactions through scripted transactions, allowing teams to proactively identify and fix issues in data systems.

How does real user monitoring help Martech systems?
Real user monitoring captures real-time data from actual users, ensuring the accuracy of analytics and helping to spot and address system issues promptly.

What are the benefits of improving observability in analytics?
Improved observability ensures data accuracy, reduces operational costs, strengthens brand trust, and allows for better resource allocation.

Is observability in Martech similar to software development?
Yes, observability in Martech borrows principles from software development, focusing on proactive system monitoring and real-time data analysis to enhance reliability.

By James Praise|2025-05-12T04:37:19-07:00January 7th, 2025|Conversion Rate Optimization, Revenue Funnel Optimization, Attribution Modeling|0 Comments

Dominating Data Overload: How to Get Actionable Insights from the B2B Marketing Funnel

Imagine this: Your content strategy is on point. You’ve meticulously crafted B2B marketing funnels, pouring effort into targeted campaigns, compelling content, demand generation, and strategic CTAs. Traffic flows steadily to your website, but converting leads needs to catch up.

You dive into your analytics dashboard, overwhelmed by a sea of marketing data points – website visits, bounce rates, and click-throughs. The list goes on. The challenge? You may be unsure how to get actionable insights from a B2B marketing funnel.

It’s not just about the data; it’s about transforming this data deluge into actionable information that illuminates what’s working (and what’s not) with your marketing efforts.

Here’s the good news: You’re not alone. Marketing automation and modern digital marketing tools generate a wealth of data, but extracting meaningful insights that translate to business growth can feel like searching for gold nuggets in a riverbed.

The key? Marketing teams should have a strategic selection process, allowing them to identify the data points that truly matter for optimizing the B2B marketing funnel and increasing that coveted conversion rate. Let’s look at how this works.

B2B Marketing Funnel Data Landscape

Your B2B marketing and sales funnel represents the customer journey, encompassing every touchpoint a potential lead has with your brand. Each stage in the marketing funnel strategy – Awareness, Consideration, and Decision – generates valuable data that sheds light on user behavior and engagement. Let’s look at the funnel stages and the key data points you can gather.

Awareness Stage

This stage is powered by content marketing strategies for creating awareness and is all about attracting potential customers. Search engine optimization can help get your brand and site noticed. Funnel metrics to track include website traffic sources (organic search, social media, referrals), customer data demographics (industry, company size), and content engagement metrics (time spent on the website, blog post views, video play rates).

Consideration Stage

As the action stage of the customer journey, visitors in this stage are actively researching solutions to their challenges.

Key data points to monitor include:

Landing page conversions (e.g., comprehensive guides and ebook downloads, webinar registrations),
Time spent on key content (product pages, case studies, frequently asked questions),
CTAs clicked (demo requests, free trial signups).

Lead nurturing email marketing campaigns can help move customers to the next phase.

Decision Stage

This stage in the journey is when qualified leads move towards a purchase decision, an essential stage in the sales process. Important data points include demo signups, free trial activations, and quote requests to gauge interest and sales readiness.

Sales teams should remember that customer retention should be considered part of the sales cycle to capitalize on all the work done during customer acquisition. Be sure the customer service options are on point. Set up a system to review and analyze customer feedback regularly.

Remember: Data quality is paramount. Inaccurate data leads to faulty insights. As a B2B marketer, it’s your job to ensure that your analytics tools are properly configured and integrated to collect clean, reliable data. This data is the foundation for trustworthy analysis and the key to your success.

Goal-Driven Data Selection

Data is powerful, but without a clear direction, it can become overwhelming. Here’s where the magic happens – aligning your data selection with your specific marketing funnel goals.

Setting SMART Goals

The foundation of practical data analysis is establishing clear, actionable SMART goals.

Most of us are familiar with the SMART goals framework. Here’s a breakdown:

Specific: Define your goals precisely. Don’t settle for “increase website traffic.” Instead, aim to “increase qualified leads generated from organic search by 20% within Q3.”

Measurable: Ensure you can quantify your goals with relevant metrics.

Attainable: Set ambitious yet achievable goals within your resources and timeline.

Relevant: Align your goals with your overall marketing strategy and business objectives.

Time-bound: Establish a clear timeframe for achieving your goals.

Aligning Data with Goals

Choosing the right data points becomes straightforward once you have defined your SMART goals. The fundamental principle is to select metrics directly related to your funnel goals.

For example, if the goal is to increase brand awareness among decision-makers in the healthcare industry, the data point would be organic traffic from healthcare industry publications.

In another example, the chart below gives a broad overview of the metrics B2B marketers should track in 2024 to evaluate content performance.

Actionable Insights from Your Marketing Funnel

Source: Content Marketing Institute

Prioritize Ruthlessly

It’s tempting to track every possible data point. However, information overload can lead to analysis paralysis. Prioritize a limited set of high-impact metrics that provide the most valuable insights for achieving your goals. Focus on metrics directly influencing conversions and answer specific questions about your funnel’s effectiveness.

How to Get Actionable Insights From a B2B Marketing Funnel

Data without interpretation is like a treasure chest without a key. Here’s a step-by-step process to unlock valuable insights from your B2B marketing funnel data:

Step 1: Data Visualization

The human brain thrives on visuals. Charts, graphs, and other data visualizations make complex information digestible, revealing trends and patterns that might otherwise go unnoticed. Leverage tools within your analytics platform or consider data visualization software to create clear and compelling representations of your chosen data points.

Step 2: Identify Trends and Patterns

With your data visualizations, it’s time to delve deeper into analyzing trends and patterns within the data sets. Ask yourself:

Are there significant drops in traffic at specific points in the funnel?
Which content pieces generate the most qualified leads?
Are there particular CTAs underperforming?

Identifying these patterns will highlight areas for improvement within your funnel.

Step 3: Ask the Right Questions

Data analysis is all about asking the right questions. Here are some prompts to get you started:

Why are visitors dropping off after a specific page?
What content resonates most with qualified Consideration leads?
Are there any technical issues hindering conversions on landing pages?
How can we improve the user experience at different stages of the funnel?
For account-based marketing, consider including the following: How well does our current funnel content resonate with our ideal customer profile (ICP)?

By asking insightful questions, you unlock the true potential of your data, uncovering insights to optimize your B2B marketing funnel, such as identifying high-value leads for nurturing through lead scoring programs.

Step 4: Hypothesis and Testing

Data-driven insights are powerful, but they’re not crystal balls. Based on your findings, the next step is formulating hypotheses about funnel improvements. Teams should test these hypotheses to validate their impact.

Here’s an example:

Hypothesis: Upgrading the design and CTAs on our product page will lead to a 15% increase in free trial signups, moving more leads into our sales funnel.

Use A/B testing or other methodologies to test your hypotheses and measure the results. This data-driven approach allows you to continuously refine your funnel for optimal conversions.

B2B Funnel Optimization – From Insights to Action

You can transform your B2B marketing funnel from a data swamp into a goldmine of valuable information by implementing a strategic data selection process and following the outlined steps for generating insights. Remember, data is only as powerful as your ability to utilize it effectively.

Dominate Data Overload and Start Seeing Results

As you’ve seen, data wrangling can be complex and time-consuming. At Funnel Envy, we believe in focusing your marketing efforts with laser precision. Our Full Funnel Conversion Audit is the perfect starting point, providing an efficient way to identify areas for improvement and maximize your return on investment.

Here’s what you’ll gain from our Full Funnel Conversion Audit:

Holistic Optimization. Discover how to break down silos and optimize every stage of your funnel for peak performance.
Lead Generation Mastery. Learn how to convert more top-of-funnel prospects into qualified leads ready to close.
Marketing & Sales Alignment. Develop a shared understanding of lead qualification criteria to ensure seamless team handoff.
Actionable Roadmap. Get a 21-day plan tailored to your specific needs for optimizing your entire funnel.

Ready to stop data overload and start seeing real improvements in your conversion rates?Click here to learn more about our Full Funnel Conversion Audit and unlock the full potential of your B2B marketing efforts!

By Kala P|2025-05-12T04:37:14-07:00August 5th, 2024|Revenue Funnel Optimization, Attribution Modeling|0 Comments

How To Improve Your Site Experience In A User-Centric World (And Still Generate Leads)

The algorithmic world of web optimization is rapidly moving towards a user-centric paradigm. To keep up, brands will need to prioritize their site experience like never before.

In this post, we’re going to cover why site experience is key to your success and give you some actionable tips you can use to improve your site experience today.

Let’s get into it!

Your site experience is key to generating leads

Website experience, or UX, encompasses everything your users encounter when they visit your website. It’s the visuals, the ease with which they can uncover information, and the process they go through to make a purchase.

In a world that is becoming more user-centric, focusing on user privacy and moving away from keyword-based SEO, lead generation is going to become increasingly entangled with the performance of your website. The better your site experience, the more leads you’ll generate. And, with that in mind, here are our top ways to improve your site experience…

5 ways to improve your site experience

1. A great site experience starts with pages that load quickly

The first thing that anyone is going to notice when they visit your website is how quickly it loads. Or, ideally, they won’t notice this at all.

The goal for any website should be for any page on your site to load in less than three seconds on an average WiFi download speed. If your website takes longer than this to load, you have some work to do. When it comes to mobile, things need to be even faster. Less than two seconds is ideal for reducing your bounce rate.

One of the first things you should do to reduce a web page’s load time is to compress all of the images on your website. There are free resources online (like TinyPNG) that will quickly compress images for you.

Plus, white space is also important. Not only is it important to a pleasing design, but blank space loads faster than content-filled space.

And, finally, ensure that the most important and visible elements of your webpage load first. Typically, buttons and navigation bars should appear first, then your text, then images and media.

2. Simple and efficient registration and sign-up forms are crucial

Another crucial component of a great site experience is simple registration and sign-up forms. These are the forms on your website that visitors use to sign up for your newsletter, subscribe to your service, and register an account on your website.

If these forms aren’t easy to use, then visitors aren’t going to use them. When you ask your visitors to complete a task, you aren’t just asking for their attention span, but also their mental effort. Seamlessness is key.

A simple form process uses as few fields as possible, doesn’t needlessly violate the person’s privacy, and keeps everything on one page if possible. The more information a visitor has to give and the more pages that have to load for them to give, the more likely they are to bounce.

3. Have clear CTAs –– and not too many of them!

Everyone working in the marketing industry knows that CTAs dramatically increase engagement. Direct CTAs, such as “Order this product today!” as well as indirect CTAs like colorful buttons both count. They give a webpage purpose, guide visitors down a path, and most importantly, close sales!

Despite the overt marketing at work here, visitors like CTAs. They’re on your website because they are curious about your business. CTAs make their journey simple. Click here for this information, go here to buy this, and subscribe in these three steps.

On the other hand, you can overdo your CTAs. Try to keep it to just one CTA per page, and don’t have every CTA be aimed at landing a sale. Maybe have a CTA to your newsletter on your blog instead of a CTA for a product you sell. Or, work on personalized CTAs (or smart CTAs) tailored to different audiences and their specific needs.

And use clever design and logical flow when placing your CTAs. You don’t need a big red arrow telling visitors to look at your CTA if you place the CTA where they’re already looking.

4. Follow conventions creatively over creatively ignoring them

A common pitfall that businesses run into is the idea that everything they do needs to be unique to them. So they overcompensate when doing something simple (like crafting a great site experience) and try to stand out by breaking convention.

This more often than not will scare visitors off. Design conventions exist for a reason –– because they work! And because conventions are popular practice, they’re what users expect when they visit your website.

Moving the navigation bar to the bottom of the screen adjusting all of your text to the right, and having images of your product flash around the screen will help you stand out –– but probably not in the way that you hope for.

Instead of trying to be quirky, stick to tried-and-true web design conventions. Then, put your personality into them! Follow traditional functional practices while adding unique and personalized aesthetics to your website.

A pleasing color scheme and clever animation in an otherwise standard website will take you much farther than an obtuse (albeit original) site experience.

5. Save your writing for the blog

Our last tip is pretty simple. Save your writing for your blog! Articles and content marketing perform great there, but they’re not going to perform as well on your landing pages.

Instead, try to replace text content on your home and landing pages with graphics, blurbs, and bullet-point lists. Video content performs particularly well on landing pages (not so much on your home page). Use text in short sentences to give clarity, flow, and concise information. For everything else, stick to visuals!

Eager to keep learning about how to improve your site experience?

The tips listed above are just a few of the ways that you can improve your site experience. To become a lead generating pro, you can check out the rest of the posts on the FunnelEnvy blog.

And if you’re ready to take your marketing and site performance to the next level, reach out to the FunnelEnvy team for expert advice, guidance, and optimization.

By Arun Sivashankaran|2025-05-12T04:36:55-07:00June 2nd, 2021|Full-Funnel Optimization, Revenue Funnel Optimization, Attribution Modeling, Conversion Rate Optimization|Comments Off

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|2025-05-12T04:36:55-07:00June 2nd, 2021|Revenue Funnel Optimization, Revenue Attribution, Conversion Rate Optimization|Comments Off

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|2025-05-12T04:36:53-07:00March 2nd, 2021|Revenue Funnel Optimization, Conversion Rate Optimization|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|2025-05-12T04:36:52-07:00February 17th, 2021|Conversion Rate Optimization, Revenue Funnel Optimization, Attribution Modeling|0 Comments

Revenue Funnel Optimization Focus on the Offers

Transcript

Hi, everyone, I’m Arun from Funnel Envy.

We help demand gen marketers increase pipeline and revenue through revenue funnel optimization.

And today I want to talk about why you should really focus on the offers. I’ll explain what that means as we go through this.

Now, let’s take a step inside the data driven demand generation marketing team, maybe the top problem on the CMOS radar is that the acquisition costs are too high and they’re not going to hit their pipeline or revenue goals. And so she’s asking that the head of demand gen, you know, where’s the problem?

Now, looking at the data, being a good data driven marketer he comes back with, you know, they’re spending a lot of money on unpaid and organic traffic. The quality of that traffic is good, but it’s just not converting like it should be.

So, of course, the natural question is, what can we do about it?

Now very good answer and a common answer is to focus on website conversion rate optimization. And that typically involves running a lot of online experiments.

So you can budget that, make it a priority but recognize that those executives are probably going to want to see impact based on pipeline and revenue and probably want to see it fast.

So let’s dig into online experimentation, back in twenty seventeen the Harvard Business Review published this important study and article really talking about the power of online experimentation and correlating successful business outcomes to a culture of experimentation. They cited examples like this from Bing where bing tested multiple different colors on their site, ran experiments and realized an incremental 10 million dollars in annual revenue from these experiments.

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

Well, in our opinion and in our experience, no. You’re not Google or Bing, leaving aside traffic considerations, you’re trying to influence B2B buyer behavior over a long customer journey. And the reality is that groups of buyers that are considering enterprise solutions are not going to be influenced to buy based on the button color or other small cosmetic changes. And this is really important because, of course, experimentation comes with a cost. Not only do you have the people and the technology costs of running online experiments, it’s also an impact on your ability to make decisions as an organization. So, it’s really important that when you’re doing this, you focus on the elements that are actually going to deliver revenue and influence those B2B buyers.

Now, when we think about the B2B buying journey or the revenue funnel, you can think about it as various stages and as prospects progress through those stages, they do so through a series of exchanges. This is fundamentally the heart of marketing where you are offering something to that prospect in exchange for something else that could be a piece of content in exchange for their attention or their contact information, that could be an offer to attend an event, that could be an offer to talk to the sales team, it’s some offer through which they learn more about how your solution is going to benefit them.

So from our experience and in all of the testing that we’ve done, the highest value, the highest leverage use of experimentation for the demand gen org is to improve the relevance of those offers through that revenue funnel, through that buying journey and the ease of engaging with it. And of course, we always want to make sure we’re measuring the impact of those experiments based on the KPIs that matter, pipeline and revenue.

So what does it mean to be optimizing offers? Well, we like to focus on three main aspects.

One, of course, is the offer itself, that thing that you’re proposing to exchange with that visitor or prospect for them to better understand your solution. The more relevant it is to that visitor and their intent, the more effective your ability to convert them will be.

The other important aspect of the offer is the framing of the offer, and here we’re really talking about the headlines and CTA’s headline is really important because typically a visitor is going to spend five or 10 seconds, at the most, deciding if they want to stay on your site or hit the back button and go somewhere else. So the more effectively you can position that headline and entice them to continue reading and engaging with it, the more effective you’re going to be.

Third element of the offer is the mechanism of exchange, how they actually exchange what you want from them in exchange for the offer that you are putting in front of them. Typically, this is in the form of a web form, but it doesn’t have to be. We’re also seeing more chat bots, conversational marketing tools that accomplish the same thing, provide that medium of exchange for the offer.

So let’s look at some examples.

Landing pages are a great starting point. Many of you are probably running traffic to landing pages and putting an offer in front of those visitors hitting it. Now, in this case, we recognize working with a customer that they actually had three viable offers for those visitors coming through their paid campaigns to their landing pages. And rather than only showing them one, we use data to dynamically personalize the offer itself, but also the framing and the page layout to reflect what might be most relevant to that visitor. And doing this, we see an almost 44 percent improvement in revenue per visitor when we ran this experiment.

We spend a lot of time working on the home page and specifically that above the fold section of the homepage, at the top of the page where most of the eyeballs go. Now, many of you might have a site and a home page that kind of looks like the baseline experience here where you’re trying to introduce your solution at the very highest level to that first time visitor. But of course, you probably have a lot of return visitors, especially if you’re a SAAS solution, a lot of return visitors who are already familiar with your solution or your offering. And it probably doesn’t make sense to show them that same welcome offer. And in this case, we actually were able to identify visitors and the specific solutions that they were interested in and present that offer right on the home page that otherwise would have been further down in the in the website that they would have had to navigate to. So I presented them with an offer that they were more interested in and serving those as variations right on the homepage, we see an almost 50 five percent improvement in conversions coming through this page.

Now, you can do this based on buyer stage as well, in this example, we have a customer with a freemium model where visitors who are on the free plan come to the home page and see a call to action or a button that says upgrade your plan. When they click on it, the baseline experience was to take them to standard SAAS Plan tiers and they could select the one that they would upgrade to.

Now, using data, what we were able to do is identify the plan, which was most relevant for any individual visitor, and show them instead of a plan selection, show them the specific plan that they should upgrade to right on that home page, as well as the benefits they would get out of that plan. CTA was changed to from upgrade your plan to upgrade to a specific plan at a specific price point. And in doing this, we’re able to bypass the plan selection, kind of choose your own adventure experience and take them directly to the credit card entry and upgrade.

So by removing friction, presenting them with a more relevant offer, we’re able to see and almost 70 percent improvement in revenue per visitor coming through this experience.

Of course, that mechanism of exchange is often the form, and so we spend a lot of time optimizing forms. Now recognize there’s often a lot of friction on behalf of the visitor when they see a form and they start to enter personal information, even if they’re interested in the offer. The act of giving someone your email and other personal information often presents a big hurdle. And this is where you see a lot of drop off in terms of conversion. So one of the things that we like to do is take those contact forms and reinforce the benefit and the value to the visitor of filling out that form.

So you can see an example of that where we take a default contact form, which is kind of generic and make it very focused on the benefits and ran this experiment. Here we see about an 85 percent improvement in conversions coming through this form.

Final example, you know, if you have the data, you can get pretty sophisticated with this. Many times we see experiences like the baseline product homepage that you see here where it’s a solution that actually speaks to multiple personas within the organization. And your team actually has different offers for each of those personas.

Now, when you try to put it on a single page, they all compete for attention and kind of blend in and none of them gets the conversions or attention that they deserve. By using data, we were able to identify the offer that was most relevant to the specific visitor or persona coming to this page and replace that experience with multiple calls to action with a single focused offer that was most relevant to that persona, in this case, a developer or an analyst or a manager. Here running this experiment with those variations we see in almost 50 percent improvement in revenue per visitor.

So the offers are really important to focus on as the highest leverage area of experimentation for the Demand gen marketer on your site.

And I want to wrap up with some final points.

It’s really important before you undertake this kind of experimentation to make sure you have solid revenue insights. What that means is make sure you’re able to evaluate your existing offers based on their pipeline and revenue contribution and that you’re set up to measure your experiment not just based on onsite conversion, but based on their impact to pipeline and revenue.

You saw some examples of segmentation that I walked through and personalization.

Our recommendation is to prioritize your segmentation based on how the differentiation of intent across those segments and the size of your addressable audience. We often find that people are running segmentation only for like five or 10 percent of their audience. That’s not going to be as effective as if you can address 90, 95 percent of the visitors coming to your site. This is why we start with buyer stages as our starting point for segmentation, because it presents both great opportunities for differentiated Intent buyers at different stages, want to see different content and engage in different ways. And it maximizes your addressable audience. The vast majority of the visitors coming to your site fit into anonymous, known lead, active opportunity or customer.

Finally, there are a lot of common sense opportunities if you start thinking about buying stages for more relevant offers and some obvious gaps that you should be able to identify.

Start by asking yourself some simple questions.

Should a known lead see a lead capture form? Does that make any sense or can we repurpose those pixels and that experience for something that’s more relevant?

Similarly, should an existing customer see the requested demo call to action or talk to sales? Maybe not. Maybe there’s an opportunity to up sell them or, you know, get them to support or other resources that may be more relevant.

And with that, I want to thank you for listening today, bye.

By Arun Sivashankaran|2025-05-12T04:36:51-07:00February 10th, 2021|Revenue Funnel Optimization, Conversion Rate Optimization|0 Comments

How Hotjar Can Help You Convert More Leads

Hotjar is a great complement to Google Analytics. Layering qualitative and visual data over the raw numbers gives you another dimension of insights.

But just like with your Google Analytics data, if you ignore key segments, you do so at your own risk.

Imagine, for example, that a heat map shows you that only 20 out of every 1,000 of visitors click on your Product Tour CTA. In fact, the scroll map shows you that only 15% of visitors even reach that section of the page.

You might conclude that the section and CTA don’t matter, and consider removing them.

Now imagine that all 20 of those visitors are leads – visitors who have identified themselves by signing up for a free trial, downloading a resource, or attending a webinar. Suppose that on average 15 of those 20 leads end up turning into opportunities. The Product Tour just went from wasted space to one of the highest-value interactions on the site!

Fortunately, it just takes a bit of work to begin segmenting your most valuable visitor data in Hotjar. Let’s look at how to do this with leads.

Why leads?

While leads might not be your most important identifiable visitor segment, for most B2B SaaS sites they deserve special attention. In fact, they’re already getting special treatment in your nurture campaigns. (Right?) And hopefully you’re personalizing offers and CTAs for them as well.

Still, the steps below will work for any segment you can identify. Target accounts, industry of interest, or existing customers can all be given VIP status in Hotjar.

Setup

Before you begin, make sure you have two things in place.

1. Hotjar Plus or Business

The free plan doesn’t support custom tags and triggers.

2. A way to identify leads on your website

Not sure how to do that? This post will walk you through it. And if you’re using Marketo, FunnelEnvy automatically syncs lead status with all your frontend tools – Google Analytics, Drift, Google Optimize, and yes, Hotjar.

Tag session recordings

Watching playback of visitor sessions is a great way to put yourself in your customer’s shoes. It’s also dauntingly time consuming. One day’s worth of recordings could take a month to view.

So clearly you need to prioritize what you focus on. Watching a half dozen leads interact with your website will yield more insight than watching a hundred anonymous visitors land, scroll, and bounce.

All you need to do is execute a single line of code when you identify a lead on the site:

hj('tagRecording', ['leads']);

Set this up, and you’ll be able to filter recordings later.

Screenshot of Hotjar recordings filtered for leads

(See the Hotjar docs for more detail on how this works.)

Trigger heat maps

Instead of mixing clicks from anonymous visitors, customers, and leads all into a single heat map, you can create one for leads only.

You’ll need to create a heat map with a JavaScript trigger, then fire the trigger when leads visit the page in question.

If you’re using FunnelEnvy for Marketo, it’s as easy as adding a Trigger to Google Tag Manager:

Screenshot of a Trigger in Google Tag Manager

(FunnelEnvy for Marketo can push visitor stage to the Data Layer, meaning you can use it to trigger any Tag)

Then create a Custom HTML Tag to fire the Hotjar code:

Screenshot of a Custom HTML Tag in Google Tag Manager

Create a custom poll for leads only

What page has the highest exit rate? What page do visitors spend the most time on? What are they looking for, and not finding?

The answer is probably different for leads compared with anonymous visitors. The only way to find out is to ask.

Lucky for you, you can trigger a custom poll with the same code that triggers custom heat maps.

So if you’ve added the Google Tag Manager logic shown above, all you have do to is create a poll with a JavaScript trigger. And you’re done!

Ask every visitor this question, get a lot of noise. Ask leads only, find out what matters

Where to start

There’s a lot you can do to better understand (and more effectively convert) leads on your website. As a first step, just tag and watch some session recordings to see how leads navigate your site.

This requires a way to identify those leads in the first place. Solve that problem once, though, and you open up deeper insights in Google Analytics, custom playbooks in Drift, and personalization options in Google Optimize.

If you’re using Marketo, FunnelEnvy solves this for you. No need to bring in the dev team and turn it into a multi-month project. If you’re ready to start giving leads the special treatment they deserve, just get in touch.

By Brian Hall|2025-05-12T04:36:51-07:00July 13th, 2020|Revenue Funnel Optimization, Attribution Modeling|0 Comments

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