The Holistic Marketing Data Model
What once was a solidified concrete model, the marketing mix is quickly morphing and changing every year. As digital marketers, we have to be critical of these changes and of the marketing intelligence we collect. Some campaign analyses emphasize metrics like impressions or simple click data. Social media has created even more grey area with the emergence of “engagement” metrics. Applying too much focus on these simple metrics can result in poor decision making.
How do we fight through the clutter? Adopt a holistic data model (duh).
A holistic data model incorporates strategic data collection with applicable decision making. Data is chosen to answer questions [link to “Ask the right questions, collect the right data”] and represent marketing KPIs. Follow these steps to set up an effective model:
1. Define Key Stages in Customer Life Cycle
Think about how your ideal customer moves through the buying process. Consider the stages of their personal buying cycle, even after the product has been purchased. By understanding a consumer’s motives from “Suspect” to “Advocate” you’ll have more opportunity to capitalize on the right moments. For each life cycle stage, preferred audience behaviors should be monitored against marketing activities to judge the effectiveness of campaigns, channels, and overall strategy.
2. Assign KPIs Within Each Life Cycle Stage
With every stage in the customer life cycle, comes changes to the customer’s perception of your brand. Since your brand is consistent across all channels and life cycle stages, it’s important to set up key performance indicators. These KPIs measure the effectiveness of marketing channels and campaigns that were designed to impact the audience behavior at different life cycle stages.
Without set KPIs, you have no idea what’s truly working, and what’s not.
3. Measure Progress Towards KPIs Using Marketing Funnels
While digital marketer is constantly changing and adapting, the marketing funnel is a concept that can be carried over different industries, timelines, and projects. A funnel view is not broad enough to contain all of the touch points that are a part of your brand’s ecosystem. Still, a funnel is useful for classifying marketing metrics of varying importance.
Top of funnel metrics such as impressions and audience sizes are useful for building your brand. Creating awareness of your business should be focused here.
Middle of funnel metrics indicate user action. Things like clicks, shares, likes, etc. all represent some sort of audience interaction. These metrics, as well as some bottom of the funnel metrics, help explain the relationship you have between a campaign’s likelihood to attract visitors versus the likelihood to convert those visitors via a preferred behavior.
Bottom of funnel metrics are generally conversion metrics. These are actions that represent sales intent. Remember, a conversion is generally defined as any action where a user gives information (or sweet, sweet money) in exchange for your services.
All in all, a holistic marketing data model is strategic. Never jump into a campaign blind. You want to have a clear understanding of your goals, how you’re going to measure those goals, and what actions you will take to affect any outcomes.