Fashion Digital NYC: Top Questions About Retention Marketing

Earlier this week I had the privilege of speaking at Fashion Digital NYC  with our client, Adam Schwartz, COO of BustedTees. We were there to talk retention, a topic that’s near and dear to my heart. Why you ask? Because it’s 5x more cost-effective to retain an existing customer than to acquire a new one, yet only 16% of companies are putting primary focus on retention. Big mistake with huge implications for both the top and bottom lines.

Leveraging customer retention data to optimize acquisition efforts is table stakes to an effective CRM program. It’s a perspective that many marketers still have not yet adopted, but it’s what winning marketers, like those at BustedTees, are using to drive acquisition investment decisions.

In our talk Adam and I covered key frameworks every marketer needs to be successful today, ranging from calculating the true long-term costs of customer acquisition (and how those vary by channel) to how to delineate between short-term conversion wins and long-term lifetime value wins as well as tools for determining the tradeoffs of quantity and quality in the marketing funnel. Marketers need to be driving incremental business revenue while protecting long-term customer value – that’s no easy feat, and it’s all too easy to get lost in the here and now of optimization wins that happen today.

We presented our perspectives in a workshop format, so we got to field many excellent questions. I suspect that many of our blog readers might have these same questions, so I thought we could address the top three here:

1. How can a marketer or marketing organization conduct in-depth analysis of these optimizations, tradeoffs, etc. with limited resources (especially time)?

  • Gluing together data from various sources can be a mess; we hear it from our clients who come from legacy email service providers every day. From Access files to Excel sheets and massive professional services fees, you’re right: trying to get all the data into one place and into a digestible format can cost you so much time that the idea of analyzing it is unpalatable. Our answer to this common challenge was to build our own BI productto sit on top of all of our customers’ customer and purchase data within Marigold Engage by Sailthru. Our tool, Marigold Engage by Sailthru Advanced Analytics, lets marketers slice and dice data with just a few clicks. This is powerful especially when you want to look at how ROI differs by acquisition source, omnichannel tendencies, etc. A partner who can get you to a place of action more efficiently and accurately is a partner you need. Clients regularly use Advanced Analytics to look at lifetime value and revenue degradation by acquisition source, all the way down to the keyword level; this in turn helps inform ad spend as well as how to tweak your approach during seasonal times (e.g. the upcoming holiday season).

 2. When you decide to invest in doing treatment tests on cohorts (vs. just A/B splits), which criteria do you use to segment?

  • This question followed an example I gave around testing a content treatment in addition to just a product merchandising treatment as a tactic for mitigating email fatigue. As I told the audience at Fashion Digital, I recommend trying several different segments and seeing what sticks – and of course you always want to keep test groups large enough to be statistically significant but small enough to be comfortable with the unknowns they might bring. For instance, if you were going to test that content treatment I mentioned, you could try that approach with new users, just women, lapsed buyers, etc. and see what results in the highest impact.

3. How do you get organizational buy-in to invest time in this kind of in-depth testing and analysis?

  • Truth through proof! For clients who are struggling to get internal buy-in, the best way to gain consensus is to build a thorough business case about the revenue potential. We increasingly see more marketers collaborating closely with their financial planning and analysis teams to help with this effort, as direct marketing/paid acquisition is obviously a huge driver of both the top and bottom lines. In general, we see the most successful marketing teams as those who get together regularly and compare data from across the functional areas (acquisition, email, merchandising, etc.) so that everyone is informed by the longer-term data. Building a culture that celebrates data-driven proof points will empower you to make a case for investing in deep analysis (and having a tool that makes this analysis that much easier certainly doesn’t hurt!).

— Cassie Lancellotti-Young, EVP of Customer Success at Sailthru