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About Arun Sivashankaran

I'm a tech entrepreneur who has been building, measuring and selling consumer and enterprise websites for years. Over the course of my career I've helped companies large and small increase revenue and engage customers as a manager, advisor and consultant.

B2B Marketers Should Stop A/B Testing in 2018


Several years ago I was hired to help fix some serious website conversion issues for a B2B SaaS client.

A year earlier the client had redesigned their website pricing page and quickly noticed a significant drop in conversions.

They estimated the redesign cost them approximately $100,000 per month.

The pricing page itself was quite standard; there were several graduating plan tiers with some self-service options and a sales contact form for the enterprise plans.

Pricing Page

Pricing Page


Before coming to us, they accelerated A/B testing on the page.  After investing a considerable amount in tools and new team members they had several experiments that showed an increase in the tested goals.  Unfortunately, they were not able to find any evidence that these experiments had generated long-term pipeline or revenue impact.

I advised them of our conversion optimization approach – the types of A/B tests that we could run and plan to recapture their lost conversions.  The marketing team asked lots of questions, but the VP of Marketing stayed silent.  He finally turned to me and said:

“I’m on the hook to increase enterprise pipeline and self-sign up customers by 30% this quarter.  What I really want, is a website that speaks to each customer and only shows the unique features, benefits and plans that’s best for them.  How do we do that?”

He wanted an order of magnitude better solution.  He recognized that his company had to get closer to their customers to win and he wanted a web experience that helped them get there.

I did not think they were ready for that.  I told him that we should start with better A/B testing because what he wanted to do would be very complicated, risky and expensive.

Though that felt like the right answer at the time, it is definitely not the right answer today.

Why Website Experimentation Isn’t Enough for B2B

At a time when the web is vital to almost all businesses, rigorous online experiments should be standard operating procedure.

The often cited Harvard Business review quote from the widely distributed article The Surprising Power of Online Experiments supports years of evidence from digital leaders suggesting that high velocity testing is one of the keys to business growth.

The traditional process of website experimentation involves:

  1.    Gathering Evidence. – “Let’s look at the data to see why we’re losing conversions on this page.
  1.    Forming Hypotheses. – “If we moved the plans higher up on the page we would see more conversions because visitors are not scrolling down.”
  1.    Building and Running Experiments. – “Let’s test a version with the plans higher up on the page.”
  1.    Evaluating Results to Inform the Hypothesis. – “Moving the plans up raised sign ups by 5% but didn’t increase enterprise leads.  What if we reworded the benefits of that plan?”

Every conversion optimization practitioner follows some flavor of this methodology.

Typically, within these experiments, traffic is randomly allocated to one or more variations, as well as the control experience.  Tests conclude when there is either a statistically significant change in an onsite conversion goal or the test is deemed inconclusive (which happens frequently).

If you have strong, evidence-based hypotheses and are able to experiment quickly, this will work well enough in some cases.  Over the years we have applied this approach over thousands of experiments and many clients to generate millions of dollars in return.

However, this is not enough for B2B.  Seeking statistically significant outcomes on onsite metrics often means that traditional website experimentation becomes a traffic-based exercise, not necessarily a value-based one.  While it may still be good enough for B2C sites (e.g. retail ecommerce, travel), where traffic and revenue are highly correlated, it falls apart in many B2B scenarios.

The Biggest Challenges with B2B Website Experimentation

B2B marketers currently face three main challenges with website experimentation as it is currently practiced:

  1.    It does not optimize the KPIs that matter well. – Experimentation does not easily accommodate down-funnel outcomes (revenue pipeline, LTV) or the complexity of B2B traffic and customer journey.
  1.    It is resource-intensive to do right. – Ensuring that you are generating long-term and meaningful business impact from experimentation requires more than just the ability to build and start tests.
  1.    It takes a long time to get results. – Traffic limitations, achieving statistical significance and a linear testing process makes getting results from experimentation a long process.


I.  KPIs That Matter

The most important outcome to optimize for is revenue.  Ideally, that is the goal we are evaluating experiments against.

In practice, many B2B demand generation marketers are not using revenue as their primary KPI (because it is shared with the sales team), so it is often qualified leads, pipeline opportunities or marketing influenced revenue instead.  In a SaaS business it should be recurring revenue (LTV).

If you cannot measure it, then you cannot optimize it.  Most testing tools were built for B2C and have real problems measuring anything that happens after a lead is created and further down the funnel, off-website or over a longer period of time.

Many companies spend a great deal of resources on optimizing onsite conversions but make too many assumptions about what happens down funnel.  Just because you generate 20% more website form fills does not mean that you are going to see 20% more deals, revenue or LTV.

You can get visibility into down funnel impact through attribution, but in my experience, it tends to be cumbersome and the analysis is done post-hoc (once the experiment is completed), as opposed to being integrated into the testing process.

If you cannot optimize for the KPIs that matter, the effort that the team puts into setting up and managing tests will likely not yield your B2B company true ROI.

Traffic Complexity and Visitor Context

Unlike most B2C, B2B websites have to contend with all sorts of different visitors across multiple dimensions and often with a long and varied customer journey.  This customer differentiation results in significantly different motivations, expectations and approaches.  Small business end-users might expect a free trial and low priced plan.  Enterprise customers often want security and support and expect to speak to sales.  Existing customers or free trial users want to know why they should upgrade or purchase a complementary product.

An added source of complexity (especially if you are targeting enterprise), is the need to market and deliver experiences to both accounts and individuals.  With over 6 decision makers involved in an enterprise deal, you must be able to speak to both the motivations of the persona/role as well as their account.

One of the easiest ways to come face-to-face with these challenges is to look at the common SaaS pricing page.

Despite my assertions several years ago, the benefits of A/B testing are going to be limited here.  You can change the names or colors of the plans or move them up the page, but ultimately, you are going to be stuck optimizing at the margin – testing hypotheses with low potential impact.

As the VP of Marketing wanted to do with us years ago, we would be better off showing the best plan, benefits and next steps to individual visitors based on their role, company and prior history.  That requires optimization based on visitor context, commonly known as website personalization.

Rules-based Website Personalization

The current standard for personalization is “rules-based” – marketers define fixed criteria (rules) for audiences and create targeted experiences for these them.  B2B audiences are often account, or individual based, such as target industries, accounts, existing customers or job functions.

Unfortunately, website personalization suffers from a lack of adoption and success in the B2B market.  67% of B2B marketers do not use website personalization technology, and only 21% of those that do are satisfied with results (vs 53% for B2C).

Looking at websites that have a major marketing automation platform and reasonably high traffic, you can see the discrepancy between those using commercial A/B testing vs Personalization:

The much higher percentage of sites that use A/B testing vs personalization, suggests that although the value of experimentation is relatively well understood, marketers have not been able to see the same value from personalization.

What accounts for this?  

Marketers who support experimentation subscribe to the idea of gathering evidence to establish causality between website experiences and business improvement.  Unfortunately, rules-based personalization makes the resource-investment and time to value challenges involved with doing this even harder.

II.  Achieving Long-term Impact from Experimentation is Hard and Resource-intensive

At a minimum, to be able to simply launch and interpret basic experiments, a testing team should have skills in UX, front-end development and analytics – and as it turns out, that is not even enough.

Testing platforms have greatly increased access for anyone to start experiments.  However, what most people do not realize is that the majority of ‘winning’ experiments are effectively worthless (80% per Qubit Research) and have no sustainable business impact. The minority that do make an impact tend to be relatively small in magnitude.

It is not uncommon for marketers to string together a series of “winning” experiments (positive, statistically significant change reported by the testing tool) and yet see no long-term impact to the overall conversion rate.  This can happen through testing errors or by simply changing business and traffic conditions.

As a result, companies with mature optimization programs will typically also need to invest heavily in statisticians and data scientists to validate and assess the long-term impact of test results.

Rules-based personalization requires even more resources to manage experimentation across multiple segments.  It is quite tedious for marketers to set up and manage audience definitions and ensure they stay relevant as data sources and traffic conditions change.

We have worked with large B2C sites with over 50 members on their optimization team.  In a high volume transactional site with homogeneous traffic, the investment can be justified.  For the B2B CMO, that is a much harder pill to swallow.

III. Experimentation Takes a Long Time

In addition to being resource intensive, getting B2B results (aka revenue) from website testing takes a long time.

In general, B2B websites have less traffic than their B2C counterparts.  Traffic does have a significant impact on the speed of your testing, however, for our purposes that is not something I am going to dwell on, as it is relatively well travelled ground.

Of course, you do things to increase traffic, but many of us sell B2B products in specific niches that are not going to have the broad reach of a consumer ecommerce site.

What is more interesting, is why we think traffic is important and the impact that has on the time to get results from testing.

You can wait weeks for significance on an onsite goal (which as I have discussed, has questionable value).  The effect that this has on our ability to generate long term outcomes, however, is profound.  By nature, A/B testing is a sequential, iterative process, which should be followed deliberately to drive learnings and results.

The consequence of all of this is that you have to wait for tests to be complete and for results to be analyzed and discussed before you have substantive evidence to inform the next hypothesis.  Of course, tests are often run in parallel, but for any given set of hypotheses it is essentially a sequential effort that requires learnings be applied linearly.


This inherently linear nature of testing, combined with the time it takes to produce statistically significant results and the low experiment win rate, makes actually getting meaningful results from a B2B testing program a long process.

It is also worth noting that with audience-based personalization you will be dividing traffic across segments and experiments.  This means that you will have even less traffic for each individual experiment and it will take even longer for those experiments to reach significance.

Is there Better Way to Improve B2B Website Conversions?

The short answer?  Yes.

At FunnelEnvy, we believe that with context about the visitor and an understanding of prior outcomes, we can make better decisions than with the randomized testing that websites are using today.  We can use algorithms that are learning and improving every decision tree, continuously, to achieve better results with less manual effort from our clients.

Our “experimentation 2.0” solution leverages a real-time prediction model.  Predictive models use the past to predict future outcomes based on available signals.  If you have ever used predictive lead scoring or been on a travel site and seen “there is an 80% chance this fare will increase in the next 7 days,” then you have seen prediction models in action.

In this case, what we are predicting, is the best website visitor experience that will lead to an optimal outcome.  Rather than testing populations in aggregate, we are making experience predictions on a 1:1 basis based on all of the available context and historical outcomes.  Our variation scores take into account expected conversion value as well as conversion probability, and we continuously learn from actual outcomes to improve our next predictions.

Ultimately, the quality of these predictions is based on the quality of the signals that we provide the model and the outcomes that we are tracking.  By bringing together behavioral, 1st party and 3rd party data we are building a Unified Customer Profile (UCP) for each visitor and letting the algorithm determine which attributes are relevant signals.  To ensure that our predictive model is optimizing for the most important outcomes, we incorporate Full Funnel Goal Tracking for individual (MQL, SQL) and account (opportunities, revenue, LTV) outcomes.

Example:  Box’s Homepage Experience

To see what a predictive optimization approach can do, let’s look at a hypothetical example:

Box.com has an above the fold Call to Action (CTA) that takes you to their pricing page.  This is a sensible approach when you do not have a lot of context about the visitor because from the pricing page, you can navigate to the right plan and option that is most relevant.

Of course, they are putting a lot of burden on the visitor to make a decision.  There are a total of 9 plans and 11 CTAs on that pricing page alone, and not every visitor is ready to select one – many still need to be educated on the solution.  We could almost certainly increase conversions if we made that above the fold experience more relevant to a visitor’s motivations.

SMB visitors might be ready to start the free trial once they have seen the demo, the enterprise infosec team might be interested in learning about Box’s security features first, customers who are not ready to speak to sales or sign up might benefit from the online demo, and decision makers at enterprise accounts and who are engaged might be ready to fill out the sales form.

Modifying the homepage sub-headline and CTA to accommodate these experiences could look something like the image below.  Note that they take you down completely different visitor journeys, something you would never do with a traditional A/B test.

If we had context about the visitor and historical data we could predict the highest probability experience that would lead to both onsite conversion as well as down funnel success.  The prediction would be made on a 1:1 basis as the model determines which attributes are relevant signals.

Finally, because we are automating the learning and prediction model, this would be no more difficult than adding variations to an A/B test, and far simpler and with higher precision than rules-based personalization.  The team would be alleviated from having to do the analytical heavy lifting, new variations could be added over time and changing conditions would automatically be incorporated into the model.


Achieving “10X” improvements in today’s very crowded B2B marketplace requires shifts in approach, process and technology.  Our ability to get closer to customers is going to depend on better experiences that you can deliver to them, which makes the rapid application of validated learnings that much more important.

“Experimentation 1.0” approaches gave human marketers the important ability to test, measure and learn, but the application of these in a B2B context raises some significant obstacles to realizing ROI.

As marketers, we should not settle for secondary indicators of success or delivering subpar experiences.  Optimizing for a download or form fill and just assuming that is going to translate into revenue is not enough anymore.  Understand your complex traffic and customer journey realities to design better experiences that maximize meaningful results, instead of trying to squeeze more out of testing button colors or hero images.

Finally, B2B marketers should no longer wait for B2C oriented experimentation platforms to adopt B2B feature sets.  “Experimentation 2.0” will overcome our human limitations to let us realize radically better results with much lower investment.

New platforms that prioritize relevant data and take advantage of machine learning at scale will alleviate the limitations of A/B testing and rules-based personalization.  Solutions built on these can augment and inform the marketers’ creative ability to engage and convert customers at a scale that manual experimentation cannot approach.

This post originally appeared on LinkedIn.

By |2018-03-07T21:03:40-08:00January 19th, 2018|Uncategorized, Experimentation|0 Comments

Benefits of Personalization in B2B Marketing

Are you unsure about the benefits of B2B Personalization for your bottom line? The example below shows exactly how a few web changes in favor of personalization can increase dramatically increase revenue.

Personalization impact on Lead Value

In the case above, we’ve got an enterprise B2B SAS business with two defined two distinct groups: non-target accounts and target accounts.

Obviously, in an official account based marketing scenario you’re going to have multiple tiers, but for this example, we will use two.

What we’re assuming is that there’s a customer lifetime value of around $200,000 for your non-target accounts and $2 million for your target accounts. That’s roughly in line with enterprise SAAS businesses.

Let’s assume that both of those cohorts have a lead-to-close conversion rate of 1%.

That gives you a lead value on an LTV basis of $2,000 for your non-target accounts, and $20,000 for your target accounts. There is an obvious and significant difference there in lead value. Your target accounts are always going to represent a much higher lead value than non-target accounts.

If you’re not really focused on personalizing the experience of target accounts, you can assume that we have a higher percentage of leads that come in that are from those non-target accounts; let’s call that 80%, which means that the other 20% are from your target accounts.

From there, you can arrive at a weighted lead value, again at an LTV basis, around $5,600 for every lead that comes in.

Now if you are able to personalize the website experience for your most important accounts, you should be able to alter that mix and maybe even get it to 50/50, where 50% of the leads coming in are from your target accounts, and 50% are from your non-target accounts.

That’s obviously going to have a dramatic impact on the weighted lead value. As you can see here that’s $11,000, significantly more than when you’re not doing account based marketing and personalization.

Personalization impact on your Website

So what does that actually mean for your website? Well, again let’s assume some numbers here.

  • 200,000 monthly unique visitors and on average.
  • 1,000 of those are converting into leads
  • This gives you a conversion rate of half a percent.

As a marketing organization, you think, “Well we can do better than that. We want to invest in conversion rate improvements and we’re going to spend $200,000 to try and increase that conversion rate.” Let’s say with that investment, you’re successful.

You’ve invested in the team, in the tools, the technology to get you there, and as a result of that program, you see a 10% improvement in conversion rates.

Results of Not Personalizing

What does that actually mean for your business? In the scenario where you’re not doing personalization, you do see a pretty significant increase in new LTV that you generate. On a present value basis with some assumptions on a 3-year subscription length, you will add about $490,000 to the business. The ROI on that effort is 145%, which is great.

Results of Personalizing

In the case where you’re actually personalizing for target accounts, you can actually drive significantly more LTV into the business; almost well over 900,000 in this model with an ROI of 380%.

Investing in ABM increases ROI by 263%!

That’s because fundamentally you’re taking advantage of the fact that you’re able to drive more leads from those target accounts because you’re personalizing for them and you’re driving deeper engagement.

As you can see, that has more than double of your ROI that you can get through personalization. This is really the reason why companies that have significantly more potential in certain accounts, should be creating more personalized experiences on the website.

By |2017-06-02T15:55:09-07:00June 2nd, 2017|Uncategorized|0 Comments

Pricing Page Conversion Tips

If you are a B2B SAAS business you should be spending a lot of time on your pricing page focused on iterative testing.

Pricing pages are vital for your bottom line. Those who end up there are late in the conversion funnel, and likely gathering the information to make a purchase decision, or at least consider that purchase.

Given its importance, you should be constantly A/B testing pricing pages, taking every incremental improvement as a win for your marketing department.

At a high level, pricing pages should be clear in terms of quickly getting users information to make a purchase decision and also not introduce additional points of friction. While simple in theory to follow, we see many of these fundamental rules not being followed here at FunnelEnvy.

As such, we have created a simple list of best practices you should follow to maximize conversions with your pricing pages.

Clear and Simple Pricing Tier Design

The specific pricing tiers on a pricing page is often an acute area of focus for testing, and somewhere that you might want to spend lots of time on.

Here are 3 helpful steps to follow with your pricing page design.

  1. Focus on clarity and simplicity.
  2. Ensure the design conveys the most critical information about those pricing tiers in order for the user to make a purchase decision.
  3. Keep the calls to action clear and differentiated enough to stand out.  

I’m going to use two of the classic B2B examples for reference points here. The first one is from HubSpot, the second one is from Salesforce. They do a great job at high converting pricing tiers.

Hubspot Pricing Page

SalesForce pricing page

In both of the examples above, it’s very clear as to what you are getting with the different pricing tiers. The CTA’s are contrasting in color versus the rest of the page, and the prices are clearly stated.

If you’re looking for test ideas and you don’t think your design hits the mark there, you might want to test alternative designs.

Align your pricing with buyer personas.

The idea here is to articulate your pricing tiers in a way that resonates with the customer’s perception of their own business. For example, ‘professional’ and ‘enterprise’ are both terms that both HubSpot and Salesforce use, and it’s very infrequently that people arrive on either of these pricing pages and get confused between which one they have to pick.

The pricing tiers are articulated and match how the user perceives their business. This helps the user not get stuck trying to choose between options.

Use a single core value metric

I recommend scaling your pricing tiers to a ‘single core value metric’. This is a single metric the user understands and reflects the value they get from the platform as they scale.

To take a HubSpot example, the pricing is based on a number of contacts, and the user intuitively understands that as they have more contacts in HubSpot, the pricing increases because the value to them increases as well.

So if you’re looking at your pricing pages and want to improve conversion there and find that your pricing tiers aren’t necessarily consistent with the buyer persona or you’re not clearly articulating a single core value metric, you may want to test reframing some of that pricing, rearticulating it, and comparing that to your current baseline.

Eliminate multiple audiences for a single page

Let’s take a look at the example above. Can you spot the problem?

Right here we’re looking at actually two different audiences being targeted, and two completely different buyer journeys being crammed into a single pricing page; a single web experience.

The basic and premium options are targeted towards small or medium-sized businesses and organizations, and the signup flow is self-registration; it occurs completely through the website.

But as you can see, they’re also trying to target enterprise customers through ‘request a demo’, and speaking to someone on the inside sales team that has a completely different experience and audience.

That should set off some alarms. If you’re in the business of driving conversions, competing calls to action, audiences, and buyer journeys on a single page does have a really negative impact on your conversion rate.

Solution: Optimize through personalization

How can we improve the experience of a pricing page with multiple buyer personas?

If you are able to identify the nature of that account or traffic coming into the site, you can show a unique experience for that specific audience.

For example, target SMBs based on previous browsing behavior and highlight the self-signup flow. Alternatively, through firmographic third party integrations, identify if a visitor is coming from an Apple or Microsoft, and really highlight the enterprise plan and the benefits for that customer.

Through personalizing the experience, the decision-making process is simplified for the visitor, and you’ll see an increase in conversions.

Clear Calls to Action

It’s really important on pricing pages to set clear expectations on the call to action as to what happens when the user clicks a button. In the HubSpot example, somewhat non-traditionally, they use two calls to action.

But in this case, they are differentiated both in design as well as the expectations. One is about trying it, engaging in the free trial. One is about signing up.

Salesforce is very clear that when you click on that button, you start the free trial process.

So if the expectation isn’t clear in your call to action language, that might be something that you want to test.

Offer human help

Now even if you get all of this right, you’re going to run into times where the user is still stuck staring at the pricing page and can’t make a decision. If you do have that happening, again, that’s really high-value traffic that you don’t necessarily want to lose.

If it’s worth it to you, you might want to test intervening with human help.

Offer to intervene, give them whatever information they need to potentially get that conversion, get them across the line!

There are a couple of ways you can go about this. Salesforce, after a couple seconds, pops up a modal window offering to put you in front of a live agent.

Alternatively, if you have chat already on the site, certainly you could pop that chat window when the user’s stuck.

Try a chat window by Olark.

Keep things simple

The reality is that people don’t read content, at best they skim. Furthurmore, no one wants to read a complicated piece of content.

The same concept goes for your pricing page. Keep it as simple and easy to understand as possible. You should be always asking your self ‘what can we do to simplify this page’.

Help Scout has one of the most simple pricing pages - grow your SaaS revenue with Stimulead

Look at the HelpScout pricing page above. It’s a simple price and sign up box. There is no confusion for the customer, the action for them to take is right in front of them.

Some companies need tiered pricing given the complexity of their offerings. Yet, if some A/B tests support increased conversions and your bottom line is not affected, consider dropping the multiple price points.

Highlight your unique values

Many times users are comparing various vendors for a specific product across some specific criteria. Once you know that specific criteria for your product, make it very obvious. If you know

If you know price is a big factor, you should it as the first thing people see on the page. If you are a storage company like Box, make the storage limits one of the first things people see.

Box pricing page

In many instances people don’t even know what they want. In the classic marketing book ‘Predictably Irrational’ by Dan Ariely he states, “Most people don’t know what they want unless they see it in context”. For example, people don’t know what basketball shoe they should buy until they see it on a professional. 

Same goes for marketing a pricing page. Many people won’t know what are the important factors to consider. It’s up to you spell it out for your customers and make the most important features front and center.

Suggest Plans to Users

It can often times be beneficial to push users towards a certain plan. By doing so you are reducing purchase friction and making it easy for users to make a decision.

Spotify pricing page

Now the question becomes which plan to recommend. There is no clear cut answer to this question, but here are a few things to consider.

  • Consider data known data about a user. Using the FunnelEnvy platform, you can bring in Marketo or Salesforce data into your pricing page tests. This gives you the ability to personalize the pricing page depending on the user/accounts. As a basic test, try changing the recommendation based on company size!
  • Recommend the most expensive option. While it is unrealistic that the majority of people chose that option, you can expect people to choose the second most expensive. This is advantageous if people are often opting for your least expensive option, and you want to incentivise them to upgrade.
  • Free Trial. While the free trial isn’t going to bring you the most money up front, it does have the least amount of friction. If you can work out the numbers, pushing people to a free trial might be your best option.

Address Fears

In the world of sales there is the concept of FUD. This stands for fear, uncertainties, and doubts. These FUDs come out when a customer is making a purchase, the bigger the purchase the greater opportunity for it to arise.

The best way to address FUD is to address it up front on the pricing page. To get started, write down all the possible fears, uncertainties, and doubts that people might have. Then write down your response to how to handle the FUD.

Here are some examples.

  1. Customer: I won’t get the ROI from this software. Response: “Average customers increase revenue by 34% with the software.”
  2. Customer: The software will be difficult to implement. Response: “We offer free implementation support to guarentee you get up and running”.

See how the customer will feel much more at ease after their fears are addressed.

SumoLogic Pricing Table

See how SumoLogic offers a free trial to reduce fears that users won’t get any value back from signing up.

Show Validation

It’s important that customers know other companies use and have success with your software. This validation helps to reduce fear for the customer about spending their money.

The easiest way to show validation is through quotes. See below how SumoLogic reduces fear that users won’t be able to get the software into production by showing a quote.

Customer Quote from SumoLogic

If you want to have the most relevant quote for a particular visitor, we recommend using personalization to show a quote based on a user industry. For example, if you know a visitor works in the travel industry, you could show a quote from someone at AirBnB.

Incentives Longer Commitments

It’s always beneficial to have customers pay for year-long commitments up front. This keeps them locked in for longer, and make it impossible to stop after only a month. While there might be some conversion drop-off for those who don’t want to pay at once, the overall benefit to your business will be tremendous.

Let’s take a look at some examples.

In this example from Dropbox, you can see that the pricing defaults to annual billing.

Dropbox Annual Billing

However, you can also switch to monthly billing, although it costs more per month.

Dropbox Monthly Billing

The goal here is to push people into the yearly billing and longer commitment.

Below is a similar example from Sumo. In this pricing page, they subtly say “paid annually” under the monthly price. While it can be construed as a ‘dirty trick’ to make someone think they are paying a monthly rate, this practice is quite common with pricing pages.

AppSumo Pricing Page



I hope you can use some of these tips in your own pricing pages. If you have any questions about how to best optimize your pricing page, please let us know in the comments, and we’ll be sure to give you some tailored suggestions.

By |2018-09-28T15:35:33-07:00May 11th, 2017|B2B|0 Comments

5 Strategies for Optimizing Your Customer Journey

Every business-to-business (B2B) company owner knows that digital marketing evolves rapidly. While client acquisition was once the most critical part of the funnel, the customer journey now takes top billing. A fully optimized customer journey does more than just generate a sale. It has the power to turn a B2B customer into a repeat client and an advocate for your company.

For B2B consumers in the digital age, the journey defines the experience. Discover five strategies for optimizing your customer journey and taking your B2B client experiences to the next level.

Create Customer Personas

No matter what type of business you run, you’re bound to have a variety of clients with different needs and objectives. To target the right types of B2B decision makers at critical points in the customer journey, understanding your customers’ goals is essential.

Most successful B2B business owners target key client types by developing customer personas. Start by thinking about what drives your customers and how your products and services can help them meet their goals. Ask yourself or your team a few questions about your customers as you divide both current and potential clients into segments:

  • What does success mean to them?

  • What drives them to purchase?

  • What is their price range?

  • What type of businesses do they run?

Use your answers to create a series of frameworks that will shape your B2B customer journeys. Focus on their goals, purchasing power, and decision-making potential to craft your marketing strategy.

Develop Customer Journey Maps

Image via Bigstock

With personas in hand, you can begin to map out customized customer journeys for each distinct group. Compile website analytics, social mentions, and testimonials to track customer journeys, and create a customer journey map to visualize the key points on the pathway.

Your customer journey can look like an infographic, a linear path, or even a circular cycle. Use the visualization method that best defines the customer journey for each persona. Since each persona’s journey will look different, you can begin to tailor your marketing messages for specific client types.

Continue to track social, web, and CRM analytics to ensure that you have an accurate picture of how the customer journey progresses in real time. When you have a better understanding of how much time it takes clients to complete the journey, you can fine-tune your marketing efforts to encourage customers to take the next leap.

Make the Most of Your Data

If your company is relatively new to the market, you may not have much historical data to build upon. However, if you’ve been selling related products for months or years, you should have plenty of numbers that can help you move your marketing initiatives forward.

Start by analyzing the actions that your past B2B customers have taken. Make note of a few important data points:

  • How long did they use your free products before becoming paying customers?

  • How long did they remain active customers before abandoning your product or service?

  • What types of clients tend to be repeat customers?

  • Which platform refers your most lucrative customers?

As you gain a better understanding of where your customers come from and why they take certain actions, put your data to work to lead clients along the customer journey. Target and retarget customers on platforms they frequent, improve your social strategy to retain customers, better your email marketing content, or even use your data to make crucial improvements to your products and services.

Know the Micro-Moments

Image via Screenshot on 5/5/17.

In its push to capture smartphone traffic, Google has begun to place increasing emphasis on what it terms micro-moments. These are key points when consumers search for in-the-moment purchasing information or seek out immediate solutions to business problems, and they’re the ideal time to draw in a new client and generate conversions.

As Google explains, consumers’ expectations are much higher than normal during these micro-moments. If you can connect with potential B2B customers during these moments, you’re more likely to satisfy clients.

To win a micro-moment, you have to anticipate your customers’ micro-moments and be there with SEO-driven content that delivers the products, services, or information your clients need. Ensure that your content is relevant to your consumers’ needs, and make their experience with your mobile platform simple and straightforward.

Analyze User Experience (UX)

Image via Bigstock

If you’ve been in business for long, you know that getting customers’ attention doesn’t always result in a conversion. In many cases, a lost conversion results from a poor user experience.

To improve UX, review your customer metrics and understand where you tend to lose both current and potential customers. If potential customers frequently click through from your social channels but rarely make a purchase, your landing page content and functionality may need some work, such as placing key decision-making content above the fold or making buttons more prominent.

If your initial conversion rate is good but your clients rarely renew subscriptions and frequently unsubscribe from your mailing list, you may not be delivering what your customers want. Improving calls to action and targeting content to key personas can improve UX.

Focus on Engagement

Whether you need to retain customers or attract new ones, engagement is a key part of the customer journey. You can keep the conversation going with clients at any part of the customer journey using a combination of social media strategy, blog posts, email marketing, and high-level content like white papers.

With each of these channels, you can continue to demonstrate how your company’s products and services help clients optimize their business and meet their objectives. When you keep clients engaged with targeted content, you can lead them along a rewarding and worthwhile customer journey.

If you’re new to developing an optimization strategy for your customer journey, rest assured that you don’t have to map it out on your own. With optimization services from FunnelEnvy, you can increase your conversion rates while improving your customer journey every step of the way.

By |2017-05-15T10:27:06-07:00May 11th, 2017|Uncategorized|1 Comment

Incorporating Account-Based Personalization Into Your Marketing Strategy

Casting a wide net in search of business-to-business (B2B) customers isn’t the right strategy for every company. Rather than spending resources on a larger market, find out why a personalized approach that targets specific accounts could better help your business achieve its sales goals.

If you’ve never used account-based marketing (ABM) before, there’s never been a better time to start. B2B companies with highly targeted audiences use ABM to create effective sales funnels that drive results. Find out how to take this marketing strategy to the next level with account-based personalization, and learn how it can help you meet high-reaching objectives.

Define Your Market

Image via Bigstock

One of the key differences between traditional digital marketing and digital ABM is that the former casts a wide net, while the latter considers individual accounts to be their own markets. To make the most of ABM, you’ll need to break your pool of both current and prospective clients into individual markets.

Doing this offers ample opportunity for personalization. Since you’ll work to build a marketing strategy for each client individually, you’ll customize digital campaigns, sales goals, and even relationship structures. Do the necessary research for each major account you want to win, and you can easily define and optimize your market.

For example, email marketing company Strongview used account-based personalization to define its target market and provide custom content with different greetings and unique images for each industry targeted.. As a result, the company experienced a 42 percent increase in web traffic, 29 percent increase in conversions from previously inactive accounts, and a 42 percent increase in engagement from target accounts.

Create a Personalized Experience for Each Account

With ABM software, you can even personalize website content for each account you’re targeting.

Easy-to-use personalization features track IP addresses for your target customers and enable your website to serve custom content to users from these select IP addresses. Doing this increases the chances that you’ll give representatives from each account exactly what they want to see, whether they’re searching for an answer to a question or they’re ready to make a purchase.

Integrate your ABM initiatives with marketing automation and sales platforms so you can easily follow up with the clients you want to land. Most ABM platforms offer seamless integrations with select platforms. Doing this automatically incorporates your target customers into each step of your marketing strategy, so you won’t miss the opportunity to follow up at key intervals.

Identify the Key Players

As you begin to develop an ABM strategy, it’s important to remember that each account or market consists of several key players. After all, most companies seek a consensus before reaching a decision, and not every person at the table will respond to marketing messages in the same way. That’s why it’s essential to identify the key decision-makers for each account and understand how best to get through to each one.

For instance, the marketing director, project manager, and CEO will each analyze your sales pitch from a different perspective. If you need all of these major players to sign off before greenlighting your project, then you need to tailor your messages to each one with headers, pictures, and white papers.

Find out who the key players are by doing basic research on the company’s website or on LinkedIn. As you shape each personalized account, review the key players with your team during internal meetings and redraft your list of target employees as necessary.

Use Retargeting

3D illustration of behavioral retargeting principle over white background.

Just because you don’t generate warm leads the first time you get the attention of prospective clients doesn’t mean you should cross them off your list. Instead of abandoning hard-to-get clients, retarget them instead.

Retargeting is a key component of ABM, as it identifies clients who have engaged with your content previously and then works to place your content in front of their eyes again. Many ABM platforms utilize ad-based retargeting strategies that serve ads to users who have previously visited your website or clicked on your content.

Some platforms even automatically provide personalized content that prompts conversions and drives sales after detecting buying signals. With this kind of personalized power, you can strike while the iron is hot and land the clients you’ve been pursuing at the precise moment they’re ready to buy.

Measure Your Results

When you use a marketing platform like Funnel Envy, Google Analytics, or a combination of both, you can easily measure the results of your ABM strategy. Social tracking tools like Kissmetrics also enable you to monitor engagement across platforms to ensure that you’ve targeted the right players.

In addition, you can quickly collect metrics that help you determine the return on investment (ROI) for each campaign. Since you’ve already done research to determine how much each account is worth to your business, you can easily do the math to calculate your return. As Alterra Group states, most executives look for revenue growth over any other measure of ROI.

By knowing campaign ROI, you’ll reduce risk and wasted resources. Don’t let a generic marketing strategy deliver results that are less than optimal. Take advantage of FunnelEnvy’s account-based personalization tool, and find out for yourself how this strategy can help you take your B2B sales to the next level.

By |2018-01-03T19:24:43-08:00May 9th, 2017|B2B|0 Comments

Webinar: Increase B2B Conversions with Personalization and Social Data

Dive deep into growth strategies used by leading B2B organizations.

B2B Marketers! Are leads coming to your site but not converting into paying customers? 

Your problem could be a lack of customer engagement across the marketing funnel. At the FunnelEnvy transformative webinar, learn the strategies we use to have explosive customer engagement for our customers like Optimizely, Hewlett-Packard Enterprise and Autodesk.

We will also be talking to Socedo’s Senior Marketing Manager, Adam Hutchinson, about how Socedo uses social data to create personalized emails that convert!

By |2017-05-03T23:35:16-07:00May 3rd, 2017|Uncategorized|0 Comments

Optimizely-CLI: Faster test iteration for developers

Today I’m going to take you through a really brief walk through and introduction of Optimizely-CLI.

A little bit of background: we at FunnelEnvy write a lot of tests in Optimizely. We love it as a platform. But we’re also software developers and engineers, and so we like to write our tests directly in JavaScript code. It’s much faster for us, and we’re really looking for ways to be able to use a lot of the tools that we use for software development in order to write tests.

We found as we built out the CLI, which stands for Command Line Interface, that being able to do a lot of the test development and debugging locally on our own machines was actually much faster. Optimizely-CLI allows you to do that, and then when you’re ready to push it up to Optimizely, you use the Optimizely API to push your test up.

You certainly do have to do a lot of the final tweaking and edits and QA directly in Optimizely, but the largest component of tests, especially more complex tests, not just changing around a word or two or a color but tests that are significantly more involved, is writing the code and is developing it. So, hopefully, if you’re a developer writing Optimizely tests, this can have value for you.

So, let’s get into it. I’m going to skip past the installation of the optcli itself. It’s pretty straightforward. It is built on Node, so you’re going to have to have Node installed locally. It’s delivered as an NPM package, so you’re going to have do an NPM install of Optimizely-CLI. Documentation is on our page, so feel free to take a look.

Once you have installed Optimizely-CLI, what you’ll want to do is create a new directory for your project. You’ll see that this one here is empty. The first thing you’ll want to do is initialize your project. The optcli init command is the one you’ll want to use for that, and you need to specify your project ID. The easiest way to find that is to head over to Optimizely and your project and go to the project settings tab, where under snippet implementation you will see your project ID.

Now, if I look at it, optcli has created a project.json file. An empty project is, obviously, not very useful, so we want to create our first experiment. Let’s say we wanted to do a headline test on the FunnelEnvy home page. To do that, you’ll want to use the optcli experiment command which takes several arguments including the directory that you want to create the experiment in, the description of the experiment, that’s what’s going to show up in Optimizely in the dashboard and in several other places, as well as the default editor URL.

When you open it up in Optimizely, this is the page that will open. You’ll see that it has created the folder and in there is the experiment.json file that describes the experiment.

Next up, we’ll want to create a variation within that experiment. To do that, we’ll use the optcli variation command, which in a similar way takes the folder name of the experiment, the folder name of the variation, as well as the variation description.

Let’s take a closer look at the files that optcli created. As you’ll see, here’s the project. Underneath there, we’ve got the headline test experiment, and underneath there we’ve got a variation called headline test. By default, optcli will include a variation.js as part of the variation, a global.css, as well as a global.js. This corresponds to the objects within Optimizely, the variation JavaScript as well as the global CSS and the global JavaScript that take effect for all variations within the project. The JSON files, as I mentioned, in here contain metadata about the variation project and experiment.

So, let’s add a little bit of code to our variation. As I said, we’re doing some headline testing. We’re going to make some changes to this headline at the top of the FunnelEnvy home page. So, we can do that right in the variation.js on our local directory, much as you would in the Optimizely edit code window, and we can add in a bit of JavaScript right there, changing the H1 tag to “Welcome to FunnelEnvy.”

Next, we’re going to want to style that, and so we can add some CSS right in the global CSS. Keep in mind that, just as with Optimizely, the global CSS will take effect for every variation. So, let’s make the font bold. Save that.

Then, just say for illustrative purposes, put a function in the global JavaScript file. And in order to call this function, I’m actually going to go back to the variation.js and call it right from there.

So, now my initial code for the variation is set. I’ve got code in the variation JavaScript, styles in the global CSS, and a function in the global JavaScript. Once you’ve coded your variation, optcli will let you host that variation locally and preview, debug, edit, and finalize the code for the variation before you push it up to Optimizely. That lets you make sure everything is right, iterate quickly on the code, and then make the final adjustments once you’re in the Optimizely environment.

Let’s take a look at what that looks like. The way to start the local server is to use the optcli host command and specify the path to the variation. By default, optcli uses port 8080. You can change that using the command line argument. And, by default, it serves over HTTP. You can also specify minus S for SSL if you are testing on HTTPS pages. If you point your browser to the URL from the console output, you’ll see that Optimizely-CLI has some instructions as well as some status and URLs for you.

On the left hand side, there are some one time setup steps. You only need to do this once, the first time you do the local hosting and script injection with Optimizely-CLI. And on the right, you’ll see the currently served experiment and variation as well as URLs to be able to view the variation on the editor URL that you specified in the experiment.

The script injection does require either the Tampermonkey Chrome extension, if you’re on a Chrome browser, or the Greasemonkey Firefox add on. In this case, I’m on Chrome, and I have installed the Chrome extension already. So, I’ll skip ahead to step two.

Step two is installing the Optimizely-CLI user script. This is generated by optcli. It’s a relatively simple script that will inject the locally served variation and CSS, locally served JavaScript, into the page by dynamically creating elements. In this case, I’ve already installed it. I’m going to hit reinstall anyway and then come back to the tab that I was on.

Now, Tampermonkey is installed on my browser. The injection script is running. I can now actually view the variation that I created. If you take a closer look at that script, optcli uses the optcli activate parameter to determine whether or not to inject the script. So, you can actually run your variation script on any URL just by appending this parameter.

Let’s go ahead and click on the link and see the variation. You can see here that this was the function that was executed in the global JavaScript, and per the variation code, the headline has been changed and the font style has been bolded. Now if I want to go back and make a change, it’s very simple to do. If I wanted to change the text in my variation to “Welcome Fellow Optimizer”, I change that locally, save the file, go back to the browser, hit refresh, and the change is done. And let’s say I wanted to get rid of the alert. It never made a lot of sense anyway. I take that out, refresh the page again, and it’s gone.

This lets you iterate really rapidly because you are doing it locally and then can therefore move a lot faster and get your code right. Let’s say I am happy with my code for the variation now and I want to send it up to Optimizely. Go back to the command line. We can stop the local server and run the optcli push experiment. It’s important to remember that you need to have pushed the experiment before you can push any of the variations underneath it. To push a variation, you just push experiment and specify the directory of the experiment.

If you haven’t entered your Optimizely API token, you’ll need to do so now. You only need to do this once on a project. It will store this locally. I’m going to enter my token now.

So, the token’s been set, and it has created a remote experiment in Optimizely. So, let’s head back over to Optimizely. Looking at the dashboard, refreshing the page, and I can see the headline test has been created. Let me push up the variation now that I created. To do that, you use the optcli push variation command specifying the path to the variation which is obviously underneath the experiment locally. And I didn’t need to enter my token, because I’ve entered it once and you can see that the variation has been created.

One final note on both the push experiment and push variation command. You can run these multiple times. The first time for both it’ll create either an experiment or a variation. But, if you make some local changes and run it again, it will actually update the code for those variations.

That’s how you can keep your local code in sync with what’s in Optimizely. So, if I go take a look in Optimizely, you’ll see that the headline test one experiment has been created as well as the change headline variation. By default, Optimizely will create a variation number one. You can remove that if you choose.

I hope you enjoyed this brief introduction to Optimizely-CLI. There are several other features there that I haven’t mentioned, so certainly feel free to give it a spin. If you have any feedback, we’d love to hear it. Feel free to submit issues or, better yet, put requests on the GitHub page. Thank you.

By |2015-02-04T13:17:43-08:00February 12th, 2015|Testing|0 Comments

How One Email Marketing Technique Can Help Recover $2.5 Trillion Dollars for Retailers

There’s one trend in email marketing that every marketer and entrepreneur needs to pay attention to: cart abandonment emails or retargeting. While the topic is always relevant, it should be top of mind for retailers moving into holiday marketing mode. Retargeting is a follow-up marketing strategy that goes after the customers who loaded items into their shopping carts on eCommerce websites, and then left without completing the purchase. The reasons for abandonment vary, from frustration with the checkout process to real-life distractions that come up while the customer is trying to finish processing a sale.

On average, across the eCommerce industry, The Baymard Institute estimates that 67% of attempted purchases end in abandonment. Other sources suggest that numbers are rising, as high as 74%. The real costs of these abandonments to the economy’s bottom line are all over the place, but one recent Inc piece estimated it was in the region of $4 trillion dollars. But according to Forbes, a startling 80% of big retailers are doing nothing about it. Even though the numbers aren’t 100% in agreement across sources, one thing is clear: they’re high, and there is a tremendous opportunity for businesses to use retargeting technology.  (more…)

By |2014-11-05T23:25:10-08:00November 6th, 2014|The Funnel|2 Comments
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