Contextual Marketing: It’s All About that Database.
In November 2015, I presented a session at the National Arts Marketing Project Conference, an annual convention for arts marketing professionals (and the people who love them). The session, "The Art of Contextual Marketing: Maximizing Relevancy in the Age of Personalization," presented with two of my colleagues, provided attendees with insight into content-based marketing. My section of the presentation focused on data: what to know, where to find it, and how to use it to supercharge contextual marketing. As supplement to the session, I wrote this piece for the Americans for the Arts blog.
Data. The word casts an attentive hush on any crowd gathered in a subdivided hotel ballroom. Data. The solution to every problem, the key to unlocking the secrets of the universe, the alpha and the omega, the Holy Grail. Data. It will make your marketing smarter, faster, better.
Well, yes and no. There are variables to whether or not your data-driven marketing strategies are good ones. One of those variables is the “heftiness” of your data, and the “heftiness” of your data depends on the source(s).
If you are like most arts marketers, the first thing to spring to mind when you think of data is whatever internal system keeps track of your revenue.
Your second thought: “Is it the right data? Does it tell me what I need to know?”
Yes and no. Transactional data is the most necessary data you can have, but many marketers become over-reliant on it.
Your third thought: “But transactional data is all I have!”
Well, no. You have more data thank you think.
THE DATA IS OUT THERE
Data-driven marketing relies on three basic types of data to improve targeting and increase revenue: first-party data, third-party data, and second-party data.
First-party Data This is data that you own. You collect it directly from your patrons in the form of ticket sales, surveys, focus groups, and staring intensely at your crowds during events.
When mining data internally, always think in addition to transactional data. For instance, Susie Patron’s ticketing history tells you that she always buys tickets to your summer performances. However, if you check Susie’s donor profile data, you might discover that she only buys summer tickets because her summer home is in your town.
You have now given your data another dimension, and maybe you don’t try to sell Susie on tickets to your winter performance.
While unique, trustworthy, and cost-effective, first-party data often lacks scale and depth. It’s great for crafting messages to individual patrons based on their relationship with us, but too small to provide insight on behavior beyond that scope.
Third-party data Third-party data is collected from many sources. Data aggregators turn vast data warehouses into digestible audience profiles that marketers can use for more precise targeting.
Third-party data provides a blend of quantitative (factual, measureable, demographic) and qualitative (anecdotal, observable, psychographic) data. It provides a broad view of how people behave and why, aiding you in developing a contextual marketing strategy that resonates across like-minded groups.
Robust third-party data and marketing profiles are sold through brokers like BlueKai, eXelate, Acxiom, and Nielsen, but open datasets can be found on sites like city-data.com, data.gov, and claritas.com. Savvy (and broke) marketers can combine data from public sources to produce segments that work for their needs.
While scalable, broad, and expansive, third-party data is not perfect. It is neither unique nor exclusive, can be prohibitively expensive, occasionally unreliable, and often so big that it’s not immediately actionable. Consumer sentiment around data collection and privacy concerns can also give third-party data an ‘ick factor’ that marketers wish to avoid.
Second-party data The simplest way to think of second-party data is that it’s someone else’s first-party data made available directly to you. Although a hot new concept in the marketing industry, arts organizations have been exchanging such data for years.
Requested a mailing list from a peer organization lately? Congratulations, you have leveraged second-party data.
Second-party data bridges the gap between “not enough” and “too much”. It’s more scalable than first-party data, and provides a better-qualified prospect base. It’s more reliable than third-party data, and the models for blind exchange of data mitigate some privacy concerns.
Second-party data offers the kind of segmentation that is often just right.
FIND THE DATA THAT ILLUMINATES PATRON CONTEXT— AND ONLY THAT DATA.
The type of data you want and how much of it you need depends on how you plan to use it. It is important to distinguish between Big Data and Too Much Information. You should always approach data research with a clearly defined question.
What are the ideal areas to leaflet with your Young Professionals affinity group brochures? What price point will the local market bear for your family-friendly concert? Are you using the best platforms to reach your underserved communities? Is there an obstacle that prevents that subgroup of always-buys-a-ticket patrons from donating? If so, how can you remove it? (Note these last are two separate questions about one problem.)
Knowing the exact question you’re asking helps you identify the best data sources and the ideal data points necessary to understand patron context and target your messaging— without being overwhelmed by data.
LET THE DATA TELL YOU ABOUT PATRON CONTEXT, NOT THE OTHER WAY AROUND.
Data-driven decision making is not a new concept, but it’s more complex thanks to the advancements of the Information Age. New data sets are available virtually every day, and it’s easy to abuse this wealth of information. Even with the best intentions, our interpretations of data can be misleading, incomplete, or outright wrong.
In some cases, rather than looking for data to discover what we don’t know, we go looking for data to confirm what we feel. If you want to become a better marketer, you have to listen to what data tells you about patron context. As Nobel Prize Laureat Ronald Coase put it: “Torture the data, and it will confess to anything.”
