Personalization Is a Business Mindset and a Long‑Term Game
January 13, 2015
Marketers often talk about personalization, but it’s startling to realize how often “personalization” simply refers to a customer’s first name in a subject line, a segment based on attributes like geography or recency and frequency, and in a best case scenario, maybe even some more behavioral “view-also-viewed” product recommendations.
These approaches have long proved valuable from a conversion perspective and undoubtedly still do, but, truth be told, they are simply campaign optimization tactics, not strategic personalization. Today’s marketing pioneers understand that true personalization means much more than just a name or a product recommendation.
The “new face” of personalization
Here at Marigold Engage by Sailthru, we think about personalization a bit differently. To us, personalization is a business mindset that must permeate every department. It’s a strategy, and a long-term one at that. The ultimate metric that matters for personalization is not so much conversions or revenue today but rather, customer lifetime value. And when personalization is done right, it drives unprecedented lift to just that.
Here are the key considerations that we use to determine what truly makes marketing experiences personal; we affectionately call it the BUS model:
Behavioral – Many implicit preferences (vs. what your customer explicitly tells you) are important to consider when driving personalization; device tendencies, geo-location factors and time of day insights are just a few examples in a long list. If you know a customer is always likely to transact at 9pm, why would you consistently send that customer emails at 7am? Relatedly, if your customer spends 5 days a month in DC on business, why are you only promoting nearby stores in her home state of Texas?
Usage – “RFM” (recency-frequency-monetary value) is still popular for segmenting customer bases and deploying targeted messages. This tactic, while effective, is just one piece of a bigger puzzle that has many more inputs (message frequency, etc.). I recommend marketers continue to leverage usage information to drive personalization (browse abandonment and win-backs are great examples), but also suggest incorporating more data on the inherent interests that underpin that usage. That is, it’s not just what the customer looks at, but what attributes do the products she views share. Are they all red? Are they all on sale? Does the customer only buy when free shipping is offered? There are myriad questions and countless variables that can be leveraged, and these drive incremental value. Sightlines, our predictive analytics product, analyzes a host of inputs beyond just RFM and has realized upwards of 50% revenue gains vis-a-vis traditional recency models.
Situational – Situational analytics seek to understand the “why” of someone’s browsing or buying behaviors. Consider this example: a customer first browses your website looking for pants near the end of the holiday rush, and most SKUs are sold out. This circumstance will undoubtedly impact future purchasing behaviors and needs to be accounted for and addressed head-on. Let’s take things a step further and assume this customer then goes to your store; rather than pushing her toward your shoe sale, you’d ideally want to capitalize on the reality that she is trying to find pants in stock! There is usually a contextual reason why customers purchase (or don’t purchase) and when that does or does not happen. Utilize this data and take action against it in subsequent campaigns.
Transitioning to the new face of personalization requires two important inputs. First, there needs to be major shift in thought: marketers and organizations need to stop thinking about personalization as an optimization tactic, and adopt it as a business mindset; in reality, oftentimes the effects of personalization are only realized in the longer term, so there needs to be a commitment to playing that longer game. Second, marketers must critically evaluate the technologies that will help make this type of personalization a reality, mostly from a database and infrastructure standpoint. More specifically, marketers must gravitate toward technologies that transcend silos and incorporate a single customer view approach to their data, or else this new face of personalization simply isn’t possible.
As a former direct marketer myself, I understand the challenges many of us experience trying to achieve true personalization. Even if 1:1 personalization is still a ways off on your radar, I urge you to take the right steps to get there (read: a single view of the customer). The ability to discern variations in customer engagement, average order value, and other key performance metrics based on how/when/where a customer buys is truly invaluable, and it will change the way you approach every business decision.
Questions about how Sailthru drives 1:1 personalization at scale for leading retailers? Feel free to leave a comment below and visit us during #eTailWest at Booth 406!
Cassie Lancellotti-Young, EVP of Customer Success at Sailthru
The State of Brand Loyalty in the U.S. in 2023
The Impact of Gamification on Retail
The popularity of gamification continues to soar and is now an essential marketing tool to drive engagement and loyalty. The appeal of interactive experiences...
Data & AI
Thanksgiving Week Shows Retailers Collecting Zero-Party Data While Loyalty Programs Continue To Provide Solid Revenue Streams
The 2022 holiday shopping season has begun and forward-thinking brands are seizing the opportunity to collect zero-party data via interactive experiences in the busiest...