A recent survey conducted by the Economist Intelligence Unit examined trends in digital marketing and identified the gaps in understanding between consumers and marketers. The survey found that as marketing strategies rely more heavily on data analytics executives find themselves struggling to interpret big data.
This got us thinking – how does this apply to display advertising? And, what’s the solution? In reference to display advertising we often speak of unstructured data as it relates to big data. Unstructured data, meaning data in it’s raw form – not bundled and packaged into groups. The reason we advocate unstructured data is that bundling data into a group(s) with other like data pieces strips data of its true value by forcing it to fit neatly into a segment. To close the gap between the large amounts of data available and gleaning insights from it marketers must learn how to interpret it. So, we’ve compiled a list of tips for starting you on the path to interpreting raw/unstructured data within your display campaigns:
- What are your campaign goals?
- What performance measurements matter most to you? Engagement? Cost Per Action/Lead? Clicks?
- Do you want to reach new customers? Re-engage existing customers?
- Are you pushing specific product/service categories or items?
- Is there a cost difference in the items your pushing?
- How will you measure success?
- For example, a CPA of $20? .1% CTR? ROAS? Link a measurable number to your goal(s)
- What’s the time frame?
- Are there any outside factors that will effect the campaign? Such as seasons, timing etc.
The survey also found a unified view of the customer is elusive, “only 27% of the marketing executives surveyed said they always integrate customer data from different sources into a centralized customer database.“
How can you create a unified view of your consumers in display campaigns? Integrate 1st party data – data from your own website on your consumers and CRM data into your display campaigns to obtain a complete and centralized view.
Tying internal data with display campaigns serves to better the performance of your display campaigns by enhancing targeting accuracy. Campaigns can be optimized to both 1st party data findings and 3rd party data findings. The addition of first party data provides visibility into the target audience’s previous behavior patterns that can be used to create more dynamic ads and further personalize campaigns. Failure to capture a unified view of the customer limits the ability to create more customized offerings that drive customer loyalty.
An online retailer launches a campaign for fall clothing for men and women. In using 1st party data in retargeting efforts the campaign goals can be tied to the existing consumer information the retailer has on hand already. Then the campaign can be optimized to the most effective messaging for each target audience instead of using a one-size-fits-all messaging and creative approach.
Overall the solution to bridging the gap between marketers and consumers in display advertising and retargeting campaigns is to understand where the gaps exist and learn to interpret data correctly in a format that does not strip data of it’s value. This allows for superior customization, relevancy and personalization which in turn drives performance and ROI.
To download the EIU survey click here