3 Answers About Personalization Every Retention-focused Marketer NeedsJun 22, 2015 - by Cassie Lancellotti-Young
Any time I speak at a conference about the power of personalization, I’m inundated with questions from marketers who want to make the leap to 1:1. When personalization (beyond just a name and location) and marketing automation was in their infancy a few years back, the questions were mostly incredulous in their nature, such as “Is 1:1 personalization, at scale, even feasible?”. But over the last year we’ve seen a big shift in the way the majority of marketers view personalization, and I’ve been so excited by the quality of questions I get asked at these industry conferences lately.
My takeaway? Marketers are no longer skeptical; they WANT to personalize. Yet many of them just don’t quite know yet how to get there, who to partner with, how to measure it, or what their personalization strategy should look like. They’re on the path to personalization, they’re just not going 60MPH just yet.
Here’s a recap of a few of the great questions I’ve gotten at events over the last 6 months (and my answers) that any marketer thinking about personalization could benefit from.
What are some examples of personalization beyond just product or content recommendations?
For a long time, personalization for retailers was synonymous with either product recommendations or rules-based logic (e.g. “dear <first name>”). Some marketers may have even introduced segmentation-based marketing, where men in LA would receive a different message than women in NY.
At Sailthru we think about personalization much more holistically. We transcend the segment and think about the individual, not just what they look at or what’s true of their demographics, but what we call the “BUS” of their engagement–Behavioral, Usage, Situational. The “usage” category refers to classic measures such as recency and frequency, but behavioral takes into account things like time of day (if I always shop at 10pm, why do I always get emails at 7am?) as well as device trends, with situational taking into account factors like seasonality, store proximity, etc.
How much work is involved in getting data into a consistent format for the single customer view so real personalization can be delivered?
We continually see prospects investing aggressively in building an all-encompassing data warehouse, an effort that can be extremely time and resource intensive. While Sailthru is not a data warehouse, our user profile functionality (the building block of all of our personalization and retention technologies) mimics a warehouse in many ways, only the data does not need to be in a consistent format. We are built on a flexible architecture that allows clients to push any data points they might have on a customer or on a transaction, regardless of the format. The ease of building this single customer view allows marketers to pump the gas on personalization that much sooner, while continuing to work on proprietary data warehouses in the background. There is no need for these to be sequential efforts; we believe these activities can very much exist in tandem when the right technology is in place.
How are you defining “cohorts” as you talk about the long-term impact of personalization?
We define cohorts as a group of customers sharing a similar attribute under an apples-to-apples time horizon. The methodologies used with cohort analysis come to light in a number of different ways but we often look at customer signup date, or when they started receiving marketing messages from your brand. When we onboard new customers and look at their historical data, we tend to see major drop-off in engagement after 30 days of marketing messages; what we’ve seen with personalization, however, is that we are able to materially mitigate the risk of disengagement after day30, which is a great place to start for cohorts. There is a very strong longitudinal effect and that has a significant impact on lifetime value
We also frequently look at first purchase cohorts to monitor trends like repeat rates, last touch cohorts, and so on. Each of these dimensions can unlock very valuable insights into different parts of the customer lifecycle.
If you have any other questions about personalization, feel free to drop them in below in the comment box!