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I started my career as an investment banker. After a few years in the field, I found myself chomping at the bit to find something more entrepreneurial. When a mentor suggested to me that I explore online marketing jobs, I admittedly initially balked at the idea. I loved getting lost in data and spreadsheets, why would I 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 rich business function that is often the principal revenue driver in many organizations.

Marketing jargon – 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.

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 five examples:

1. Retention

What I thought it meant: Driving continual revenue streams from existing customers.

Reality: 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.

2. ROI

What I thought it meant: calculating the return on any marketing decision as quickly as the data were available.

Reality: You can measure ROI in any variety of ways, but immediate ROI is significantly less interesting to me. It’s all 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?

3. Testing

What I thought it meant: My earliest understanding was that testing meant either straightforward A/B testing or more complicated multivariate testing. For both, I thought of them as near-term optimization tactics to boost metrics in the here and now.

Reality: 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.

4. Personalization 

What I thought it meant: Personalization of any kind, even if it just meant inserting my first name into a subject line.

Reality: 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 on why data is the key to short term personalization.

5. Predictions

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. 

Reality: 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

Where does this leave us? 

I cannot even begin to count the number of times where I heard entertaining combinations of these catchphrases (and many more). I used to think to myself, 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!

Context is everything in understanding marketing jargon; even my contentions here may shift in just the next few months!

Cassie Lancellotti-Young, EVP of Customer Sucess at Sailthru