How to Pick the Right Technology Stack That Fits Your Business

By Jessica Cross

On average, I receive 3 cold emails a week from vendors promising to improve conversion rates, increase sales, and turn my company into a revenue machine. Now, I’m not aiming to have this blog post be a tear down of tactics used by sales reps. In fact, I often answer those cold sales emails. Instead, I want to highlight how important it is for growth marketers to always evaluate new technology to improve performance. I’ll also outline my three lessons on how to pick the right technology for your business.

As a customer lifecycle manager at AdRoll, my job is all about building scalable and repeatable programs that address our customers across every stage of our their journey—while also looking for ways to improve the flow.

Picking the right technology for your team has a lot to do with what type of business you are trying to run. Some marketing teams focus on increasing traffic to a conversion page, such as an account sign up or software download. Other marketing teams may leverage their website as an educational tool, with the only call to action being “speak with a sales rep.”

As a growth marketer you have to think through the levers at your disposal to make incremental improvements to the flow your prospects take in becoming customers. Is it traffic to the website, people visiting your showroom, downloads of your app, free trial signups, or something completely different? Here at AdRoll we care about 30-day activation rates and the lifetime value of our customers—so those are our main levers.

Lesson number one in evaluating new technology is that you first need to understand the metrics of your funnel and find out which levers you can pull to make improvements. This will guide you in the selection of technology for your marketing stack.

We get a lot of inbound inquiries per month. A certain percentage of them sign up for an account and some of those people eventually convert to spend money over the next 12 months. With the knowledge of our site conversion rate, retention rate, and lifetime value, it makes it easier to know the impact a 2-3 point increase in conversion rate can have on overall business.

I used this methodology to justify the purchase of an A/B testing tool to run experiments on the website to incrementally improve the conversion rates of our landing pages.

This brings us us to my our second lesson step, pick a technology tool that integrates across your existing martech suite so you can see the impact of your optimizations. And to get even more specific, pick technology that can tie to reporting on revenue impact.

For example, let’s say you implement an A/B testing tool on your website and improve landing page conversion rates by 3 percentage points. Congratulations! High fives all around.

But what if you aren’t seeing your retention rates and lifetime value improve?

Well, we need to take a step back from simple landing page optimizations and look at the bigger picture of how an increase in conversion rates could impact the full revenue waterfall.

Perhaps in the process of optimizing your sign up page, you brought in a larger volume of customers with a lower lifetime value. You may have caught more fish, but it just so happened that those fish were smaller. To solve this problem you need to tie revenue earned back to each signup received.

Here are some technology pieces that work well together to do this:

While it may be tempting to pick a core tool that is the lowest cost, it won’t be very useful if it doesn’t have good integration points. Instead, look for platforms that have API endpoints, app stores, marketplaces, and the like. This is a clear indicator the platform plays well with others.

My third and final lesson is to pick technology that allows for easy testing of hypothesis and ideas. Everyone can and should contribute suggestions and ideas for things to improve your revenue flow but you will never know which idea actually works until you test it. Good growth marketing technology should include features such as hold out groups, multivariate testing, ability to calculate statistical significance, and the like. These features will allow you to build a test, roll it out to a small group, and evaluate if the test did what you originally predicted. If the test performed as you anticipated you can roll out the change across the full customer set. If it didn’t do as you hypothesized, then it’s time to go back to the drawing board and come up with another test!