The Secret to Heightened, Scalable Personalization? Standardization

scalable personalization online

By Jay Ro, VP of Experience Analytics at RAPP

Customers have always valued personalized experiences. Now, though, marketers can deliver personalization in far more scalable ways than they could just 10 years ago.

Thanks to advances in technology, engineering and — perhaps most importantly — AI and ML capabilities, platforms and brands can individualize interfaces to meet users’ needs. From websites that serve up unique, relevant content to audience-based custom color palette pages and themes, personalization tools are everywhere. And they’re driving customers through every stage of the marketing funnel.

Here’s the issue, though: Without a standardized approach to measuring all this personalization, marketers risk losing opportunities to connect and optimize their approaches. Certainly, being able to drive personalized experiences is key. Nevertheless, being able to measure personalization tactics’ effectiveness is vital to linking individualization to a bottom-line business impact.

Understanding the Static and Dynamic Elements of Personalization

Determining how to measure personalization starts with breaking personalization as a value concept into its static and dynamic elements. The static elements are those that aren’t changeable. In contrast, the dynamic ones offer a high degree of flexibility and variability to meet users’ diverse needs, desires and interests.

From a static viewpoint, two key arenas remain generally consistent. The first is the journey stage that prospects follow toward conversion. Typically, a journey starts with awareness, moves into consideration and, if all goes well, ends at conversion and (hopefully) retention. The second static aspect of personalization is the presence of what we’ll call personalization “levers” including the audience, the content and the experience. These levers exist across the whole journey.

This is where the dynamic part of personalization comes into play. Although the levers may stay the same from campaign to campaign, the nuances of those levers can be changed.

Take the audience lever. Tailored messaging and engagement approaches can target specific audience segments and cohorts. Consequently, each audience’s prospects are introduced to different sites and landing pages as part of personalization.

The same happens with the content and experience levers. Even if the majority of the content remains the same, some messages are communicated in customized ways to compel action from prospects. Ultimately, this creates what feels like a one-of-a-kind experience that facilitates bonding between the prospect and the brand.

Grounding the Elements of Personalization With Data

As mentioned above, optimizing all the static and dynamic personalization levers at scale requires a standardized, analytically supported measurement approach. By understanding how each lever, each element, impacts the whole, we can build a data-informed feedback loop to inform next-step decisions and actions that elevate our personalization capabilities granularly and iteratively.

So what are two steps to follow to launch your standardized measurements?

1. Ask the right questions upfront. To determine the right measurements, you need to have a good grasp of what you need to know. A good way to break down starting questions is by putting them into four buckets: traffic driver questions, engagement driver questions, conversion driver questions and impact driver questions.

Some sample questions you want your data to answer for each driver include:

Traffic driver: What are the most responsive audiences or cohorts? What themes are resonating with each audience? What creative content or ad units are driving media responses?

Engagement driver: What is the level of engagement when prospects arrive on the site? What types of personalization — such as changes to key site pages, content sections or navigation — could improve the visitor experience?

Conversion driver: What are the high-value actions and conversion proxy signals prospects are engaging in?

Impact driver: Are prospects realizing a value exchange with the brand?

2. Track the proper KPIs for each driver. With questions in hand, you can begin to track the primary and secondary KPIs for each driver. That way, you won’t end up wasting time or spinning your wheels on KPIs that won’t answer those questions.

Traffic driver KPI suggestions: Visitor traffic (primary); click-through rate, landing page view rate, video view rate (secondary)

Engagement driver KPI suggestions: Qualified visitor rate, aggregated content engagement rate, aggregated high-value action rate (primary); repeat visitation rates, time on site, pages per session, key site links, call-to-action engagement rates (secondary)

Conversion driver KPI suggestions: Conversion proxy signal rates like completions, starts and submissions (primary); start-to-completion rates and timeframes (secondary)

Impact driver KPI suggestions: Conversions such as incremental sales, lead generation and new account creation (primary); clicks per conversion (secondary)

Personalization always has myriad dynamic and variable elements to it. Overlaying those elements with standardized measurements brings structure to the experience and more easily highlights which variable levers are working — and which are falling short. When handled consistently, standardization can help your marketing team open new doors to untapped personalization as well as bring your brand and its customers closer.

About the Author

Jay Ro has worked for more than a decade in the marketing analytics space, with extensive experience in measurement analysis and audience targeting. At RAPP, he leads several analytic teams supporting CRM/retention, site and media/acquisition client engagements.