Data Analytics and Modeling Have a Higher Calling than Your Marketing Plan

graphic of data points

How to ensure that your toolbox is geared toward greater business outcomes

By Jordan Cardonick, VP Analytics and Technology, New Engen

The performance side of marketing has long understood and tapped into the power of “data driven marketing.” As the industry matured, what once seemed futuristic became standard practice, as data analytics, activation technology and tools, as well as brand performance all began to cooperate. Marketers who looked beyond vanity metrics to outcomes could use data insights and interconnected systems to solve problems and ultimately drive brand performance. This possibility persisted because we were able to take advantage of cookies, device IDs, data partnerships and all the tools available in the toolbox to accomplish what was previously unattainable – from integrated and ultimately omnichannel marketing, to personalized dynamic creative optimization to attribution modeling at scale. We rode this wave for quite a while – and our marketing plans were nothing if not sophisticated.

“Times have changed,” will always be marketing’s greatest understatement and reality. With the onset of GDPR, CCPA, any number of other emerging regional legislations and the ongoing tinkering of the platforms themselves, the old status quo is officially dead. Yet, for as much impact as all this recent interrelated change has had, there’s still so much that we can do with data analytics and modeling as long as we synchronize internally and with our partners and as long as we engage beyond the marketing plan and work toward the bigger picture for our businesses. The data driven promise is greater than any single marketing plan.

The trick to unlocking that promise is ensuring that your activation, media, creative, technology and measurement are synchronized. What does such synchronicity look like in the era of rolling privacy legislation? Where cookie-less may well be the new normal and consumers still expect personalized creative? Where all audiences are multi-screen and attribution has never been more complex?

Let’s take a look at the current state and the most critical areas to address and understand at a deeper level, so your data analytics can fulfill a higher purpose.

Your Part in The Bigger Picture

As the lead marketer for any business, asking yourself and your team even this one question early-on sets you up for more meaningful outcomes: Which business problems are we trying to solve as a company – and where does my marketing plan tie in to help deliver solutions?

With this one question, you are essentially taking a beat to ensure that there is direct alignment and understanding of what is best for the business versus what is the immediate goal of the campaign(s). That’s not to say there is anything wrong with pursuing Reach, effective CPMs, CTR, CVR, bounce rate, CPA etc. But, there also needs to be a measurement mechanism put in place to show how this data connects back to the overarching goals of the business. Examples may be anything from regional market share to profitability to global reach and more. Installing the right measurement strategy to connect media objectives to corporate goals is a significant challenge and well worth the investment.

An Open Mind about Your Target Audience

You surely know who your target audiences and/or consumers are. In today’s data landscape though, how do you implement the most useful data models possible to reach, engage and convert – and also discover and expand beyond that profile? What are the best practices for opening the scope, considering the changing terrain around targeting?

First, in today’s shifting landscape, it all starts with your own known and consented first-party data and using that as your starting point. A key strategy is to grow and protect this data and not necessarily just with your converted, best customers. ANY consented e-mail/first-party data becomes an opportunity to connect with an existing customer to upsell/crosssell/retain or a new potential customer to sell, so finding a way to grow that list of target-able audiences is valuable. The good news is, this is all very much in reach.

The process is very much a continued step function in terms of reaching and discovering new audiences off that core first-party seed list – and sure, the capabilities are then a bit dependent on the technology and third-party data at your disposal. We can look at some of these options below that rank from  “Best Known” to “Least Known” as far as proximity.

You might consider leveraging:

  • Your own first-party converted audiences data to better understand non-converting audiences in order to deliver them a different message. This can be done through basic exploratory analysis or more formal look-alike modeling.
  • A data partner who can help both expand your first-party data into the addressable space with already consented individuals or help uncover attributes that can be used for contextual targeting.
  • First-party data as a seed list directly into the major platforms, so that you can leverage their look-alike modeling.

Once these variously targeted campaigns are all in-market, then it’s time to  turn to your measurement framework to test, refine and optimize – all of which allows you to continually refine and even re-define your audiences, taking a more expansive and nuanced view of your universe of opportunity.

Synchronizing Sounds Great, But How Do It?

There are any number of other questions we might address but for the purposes of this piece, I would focus on this last one: How do I work with my teams and systems to synchronize and aim the concerted whole directly at the business problems I’m aiming my marketing plan to help solve?

So much of leveraging measurement and analytics really starts with business change and education. This space is complicated and it’s easy to settle on solutions that we know aren’t ideal, no matter how logical. Look no further than last touch attribution, if you need an example of this disconnect.

Step one is to rally the organization around what is the single best source that lets the organization know if it is successful or not. It could be a CRM system, an MTA or custom report, but it should be the north star that everyone consults and understands how it aggregates the data.

Step two then looks to identify the additional platforms, measurement solutions and such, that provide the insights into decision making (i.e. everything from identifying simple things like search negatives to understanding survey results that indicate awareness lift).

The final step and this is the most complicated, is to put the measurement approaches in place that aid in connecting Step 1 and Step 2. How do we ensure that if the reporting in our source of truth says “Shut off Display”, is appropriately shut down because of our ability to run a Market Test that shows that Display does provide incremental lift on overall business results (even if the direct attribution may not report out well).

No matter how much change comes our way, due to regulation, platform moves or otherwise, our respect for data driven marketing can and will live on. But, we have to look beyond the marketing plan to ensure that we are putting data analytics to the best possible use. We do this by truly embracing a role in the bigger picture, configuring measurement to align to that, taking a more expansive view of audiences and ultimately committing to the understanding that there is no report or single solution that will ever tell us the full story and that it’s a coordinated system of marketing professionals and analytics experts that is needed to address the issues today and in the future.