While working as an investment banker ten years ago and chomping at the bit to find something more entrepreneurial, a mentor suggested to me that I explore online marketing jobs. Admittedly, I initially balked at the idea. I loved getting knee-deep in data and spreadsheets, why would I want to work in advertising?
That was the first of many common misconceptions I’ve seen over the course of the past decade: marketing was not just simply advertising (which in and of itself has become extremely data-driven with the evolution of digital and programmatic). In reality, marketing is an incredibly data- and statistics-rich business function that acts as the principal revenue driver to many businesses.
Marketing vernacular - change is the only constant
In the decade since I pulled the trigger and moved into the marketing space, the vernacular and buzzwords feel like they have changed by the week. I can remember being perplexed by the idea of doing media buying through a network in 2006 (why sacrifice the transparency of a direct buy?), and chuckle when I think about the advancements that have come since.
Being a marketer has kept me on my toes and has continually challenged me to grow. When I see new faces in the industry, I encourage them to embrace their jobs with an open mind. Things change quickly, and as a result, context is king. What meant or felt like one thing five years ago means something very different today, and I know those definitions and applications will only continue to evolve with each customer Sailthru works with. Here are nine examples:
What I thought it meant: Driving continual revenue streams from existing customers.
What it really means: It’s not just about revenue; there are many behaviors that are precursors for revenue (opening emails, reading blog articles, browsing in stores), and these are incredibly important components to retention. Retention is less about revenue and more about keeping your customers engaged with your brand, so that the opportunity for conversion is never off the table. Bonus: here's a replay of a webinar I delivered that delves into the art of customer retention.
What I thought it meant: I thought customer loyalty and retention were somewhat interchangeable terms.
What it really means: There are many tactics and hacks that can be used to drive retention, but they do not guarantee loyalty (think about bargain hunters - you may be able to retain them with sales, but when a competitor has a better sale, they are out the door!). Loyalty means that your customer is loyal to your brand regardless of incentives, etc. Retention can be a combination of “push” and “pull” forces whereas loyalty means that your brand has a natural gravitational pull on loyal customers.
What I thought it meant: calculating the return on any marketing decision as quickly as the data were available.
What it really means: You can measure ROI in any variety of ways, but immediate ROI is significantly less interesting to me at this point; I care about the downstream impact of marketing tactics. Sure, you can acquire a bunch of customers cheaply through contests, but did you know they are 62% less likely convert into paying customers? What are the trade-offs of quantity vs. quality in the longer run?
What I thought it meant: Segment of customers.
What it really means: Cohorts are time-bound; sure, they may refer to a group of customers, but those customers need to be bound by a congruous time period and must be looked at in an apples-to-apples way. To put it more pragmatically, you cannot simply have a cohort of users who get a welcome email and a cohort of users who do not. You can have these cohorts if the users in Group A signed up in the exact same period as the users in Group B and are receiving the welcome email at the same exact time Group B is not. Cohorts are the heart and soul of marketing analytics, but they are not merely groups of customers.
What I thought it meant: My earliest understanding was that testing meant either straightforward A/B testing or more complicated multivariate testing; in both instances, I thought of them as near-term optimization tactics to boost metrics in the here and now.
What it really means: Both A/B and multivariate testing can drive big returns for businesses (especially when the volume is there), but I’ve come to realize another important tenet of testing: cohort-level or longitudinal testing. Sure, it’s great if Welcome #1 has a discount and boosts higher conversion than Welcome #2 which does not offer the incentive, but what is the downstream impact for the group who is initially converted on an offer vs. not? What are the differences in their one- or two-year lifetime values?
What I thought it meant: Personalization of any kind, even if it just meant inserting my first name into a subject line.
What it really means: There is undoubtedly a personalization maturity curve. Any bits of personalization - like the name in the subject line - drive lift, but the most material and longest-impact lift comes from true 1:1 personalization. In that school of personalization, no two customers experience your brand in the same way. Personalization is not merely field insertion, RFM segments or recommendations, it is the art and science of using customer data to deliver a brand experience especially tailored to the viewer in terms of all of those components - as well as timeliness, user-specific predictions and beyond. Bonus: here's a short video Sailthru produced on why data is the key to short term personalization.
What I thought it meant: Pertinent content and recommendations for each end user.
What it really means: Relevancy is about so much more than just content; it’s about leveraging behavioral, usage and situational customer data to ensure that everything about the message is relevant. Timeliness is a great example: if I always shop online after 10pm,, why do I consistently wake up to a sea of marketing and sale emails at 6:30 in the morning?
What I thought it meant: Leveraging historical data to drive forecasts on what future actions groups of customers will take (and when they will take them); this would often include using that historical data to drive product and content recommendations.
What it really means: Predictions are not just recommendations and they are not purely segment-based. Machine learning has made user-level predictions a reality, and the surfeit of data available to us allows for models to be significantly more sophisticated than just recency- or frequency-driven. We are capable of achieving a “segment of one” with predictive technologies.
What I thought it meant: Having worked with many telecom companies in my finance days, I assumed it to mean losing paid subscribers.
What it really means: No money needs to have actually been lost to qualify an event as churn! Losing customer mindshare is churn in and of itself, as if your customers are not engaged, there will ultimately be a materially negative revenue impact.
Final thoughts - for now
I cannot even begin to count the number of times where I heard entertaining combinations of these catchphrases (and many more). They were most pronounced in my past life as a direct marketer and have vendors pitching me regularly - “drive ROI across all cohorts of customers,” a lead-gen email might tell me.
What does that even mean?? But now that I’m on the other side of the fence, I find myself falling toward these phrases regularly, and have to make a concerted effort to stop and contextualize them - and to ensure that our own salesforce does the same!
Long story short: few things are as they seem in the world of marketing. That reality will persist as the landscape and surrounding technologies continue to evolve. Context is everything in understanding marketing jargon; even my contentions here may shift in just the next few months!
Editor's note: here's Cassie giving a talk on "Defining, measuring, & seizing the opportunity of personalization" with Sailthru customer Acumen Brands:
Image credit: The word Truth on a cork notice board © thinglass - Fotolia.com