A marketing road map for personalization

Having the right tools in your martech stack is essential for personalization in marketing. But columnist Nick Iyengar says be sure you don't overlook some non-technical factors that will improve your organization's personalization efforts.

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Personalization Blueshift

Personalization is all the rage in digital marketing these days, and with good reason. As an industry, we’ve reached a point where the tools necessary to launch personalization campaigns are more accessible — and affordable — than ever.

But while technical challenges were always the most obvious roadblocks for organizations trying to get started with personalization, the fact that those problems are more easily surmounted now doesn’t mean it’s always easy to launch personalization efforts — and more importantly, to see compelling results from those endeavors.

Indeed, as with most important initiatives in digital marketing, the technical aspects, while important, are in some ways only the tip of the iceberg. In addition to having the right technology in your organization’s “stack,” successful personalization initiatives include:

  • a clear view of what personalization is meant to achieve: what are you optimizing against?
  • a rigorous, data-driven approach to audience segmentation.
  • ongoing measurement to identify opportunities for refining your custom experiences.
  • realistic goals.

So, if you’re thinking about taking the plunge and investing in one of the many robust personalization platforms out in the market, consider whether your organization has also addressed these key success factors.

How will personalization move your business forward?

On the surface, the business case for personalization is straightforward. If we can provide our visitors/users/customers with more relevant, useful experiences, they should respond by engaging more deeply, converting more often, and so on.

But is your business aligned on what “engagement” means and how it’s measured? What exactly is a “conversion,” and do all the necessary teams agree on that definition?

If the answer to those questions is something other than a clear “yes,” it makes sense to think about developing a measurement framework for your organization. This framework can serve as the foundation for all measurement and optimization-related initiatives.

By going through the process of laying this foundation, you’ll ensure that all internal stakeholders are on the same page in terms of what your KPIs are, why they’ve been chosen and how they’re defined.

Without a clear, coherent measurement framework, you’ll still be able to achieve “lift” through personalization, but these wins will be at least somewhat random, sporadic and unrelated to each other.

By contrast, when everyone is acting in concert, lift achieved via personalization tends to be bigger, more frequent, and a more effective input for future, sophisticated efforts.

Audience segmentation

In addition to building internal alignment on what personalization is meant to achieve, it’s crucial to have a robust approach to segmenting your audience. For most organizations, “personalization” doesn’t mean true one-to-one personalization.

Rather, personalization means the design of customized experiences that are intended to serve a segment of your audience, based on various attributes of that segment. So which segments should you target for your personalization efforts?

Marketers often start by focusing on a few key attributes of their audience, such as the device a person is using or the traffic source which brought the person to your site/app. This approach certainly can work — after all, it’s common for mobile users to behave differently from desktop users, or for people who came in from Facebook to behave differently from those who arrived via a Google search.

But that’s the key: differences in behavior. As a result, I like to focus more on a behavior-based approach to segmentation.

For example, imagine you have a page with a few different assets that users can interact with. Maybe you’ve got a video, a PDF download and a call to action that takes people to another page or to the shopping cart. I’ll start by grouping all the people who interacted with these three elements and then analyze what they look like.

Are the segments disproportionately composed of mobile users? Visitors who came in from organic search? People in a specific geographic region? In reality, starting with predefined attributes like channel and behavioral attributes like assets clicked can get you to the same place, but starting with the key behaviors helps me and my team know where to look for lucrative segments more quickly and efficiently.

In a recent personalization project for a client, my team found that visitors from the three largest sources of traffic preferred to interact with three different elements of a campaign landing page. By the following quarter, we were able to develop personalized experiences targeted to each of the three traffic sources. In these experiences, each traffic source’s preferred content was featured more prominently, with other content deprioritized.

Overall, the personalized experiences generated a 38 percent improvement in engagement, and 4.1x improvement in response rate to the page’s primary call to action.

Ongoing measurement

Getting a personalization campaign off the ground can feel like a lot of work, so it might be tempting to use a “set it and forget it” approach to measurement, once you’ve launched. That would be a mistake!

Making time to analyze the results of your personalized experiences can yield even more valuable optimization opportunities. Ideally, you’re seeing lift in your KPIs, but perhaps even more importantly, you’re learning more and more about these key audience segments, what they want, and how to give them an even more effective experience in the future.

Realistic goals

Lastly, it’s important to remember that even if you’ve got a good measurement framework, a robust segmentation of your audience and a plan for ongoing measurement, there are still some challenges when it comes to personalization. One of the biggest ones is the creative work that has to be done.

Let’s go back to the example of the three segments who each prefer to interact with a different element of the landing page. Do you have the resources to whip up three custom experiences designed just for those segments? If so, how soon can you do that? What does that mean for how quickly you can iterate on your personalized experiences?

Don’t be discouraged if you can’t necessarily build experiences for every single segment you’ve identified, or iterate on them every single month. Rather, spend some time up front to determine what your capabilities are and what your capacity is. That way, you’ll go into things with eyes wide open and won’t have to adjust expectations that may have been built up across the organization.

In summary, there’s never been a better time to get into personalization. A few years ago, we’d have been blown away by what personalization tools can do today and how much easier they are to work with. That said, don’t overlook the non-technical side of the personalization business. As with A/B testing, personalization can trigger a virtuous cycle.

With a measurement framework guiding your efforts, a clear rationale behind your audience segmentation and a plan for ongoing measurement, the insights you gain from your early forays into personalization should feed into bigger and better results in the long run.

Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.

About the author

Nick Iyengar
Nick Iyengar is a Director of Digital Intelligence at Cardinal Path, where he is responsible for helping his clients improve their profitability by building their analytics capabilities. He returned to Cardinal Path for his second tour of duty after completing his MBA at the University of Michigan Ross School of Business in 2014. At Cardinal Path, Nick has led Google Analytics implementations for dozens of organizations in a wide variety of industries. Prior to joining Cardinal Path, Nick began his career in digital analytics at Google, where he managed Google's Analytics Guru team.

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