A few weeks ago my colleague Paul Cross, in his post Why it’s time to put the customer first reminded everyone that "brands need to put the customer at the heart of all activity."
That activity, as Paul refers to it, must include marketing analysis.
When radio, television and print media were marketers’ primary channels for reaching consumers, marketing campaigns were mostly contextual, i.e., ads for household goods appearing in family-oriented TV shows or magazines. Even in the early days of the Internet, popular websites like Yahoo! and AOL were more like digital versions of printed media with sections dedicated to:
Therefore, brand ads and promotional discounts for specific products were targeted to broad audiences that would visit web pages that were contextually relevant to those products. For example, an ad introducing a new luxury SUV would be featured in wealth management magazines and Yahoo! Autos web page.
Contextual marketing is still widely used in old and new media, and overall effectiveness of such campaigns is mainly measured by monitoring the consumers’ actions, like online and in-store purchases, after a campaign is launched.
If the consumer is exposed to only a single marketing campaign about a specific product, then this type of impact analysis may lead to accurate results. In case of concurrent campaigns promoting the same product, then an attribution analysis is needed to determine which campaign may have been more effective.
In a campaign-centric analysis approach, it is quite difficult to discover the specific audience segments that were strongly influenced by a specific marketing campaign. For example, if five million TV viewers were exposed to a new SUV ad and there were 15,000 inquiries about that car within a week, then user profile information, like age, gender, income, etc., about those 15,000 individuals is needed in order to determine an audience segment for future re-targeting programs.
Obtaining user profile information has been getting easier as more people research and shop online, especially when they volunteer to share their social profile information through a social media single sign-on process. Furthermore, across various digital channels and devices, marketers can now easily monitor consumer interactions such as:
As a result, marketers can tap into vast amounts of user data to conduct customer-centric analysis to identify specific segments that would be more receptive to particular promotions. This in turn helps marketers to better plan and optimize their marketing programs to achieve greater results.
For example, instead of just showing a new luxury SUV ad on Yahoo! Autos web page for a few days, marketers can identify and effectively target across multiple channels a specific audience segment that is interested in that type of vehicle.
With the advent of cloud-based big data processing, audience segments can be generated and updated much faster and cheaper than before. This is particularly important as marketers utilize marketing orchestration to communicate highly personalized messages that are highly relevant to a specific stage of a consumer’s journey.
For example, a consumer that has opened an email about a new luxury SUV and clicked on a link that took her to a web page to customize a particular configuration of that SUV would be in different audience segment than a consumer that has contacted a dealer for a test drive.
Three key data requirements for creating effective audience segments are coverage, quality and timeliness. Coverage deals with the breadth and depth of the information captured about an individual and includes detailed profile information (demographic, social, interests, etc.) as well as offline and online behavior (responding to ads, purchases, shared feedback, etc.).
More user information is obviously better but irrelevant data could be problematic. Quality is about the goodness and reliability of the user data, particularly demographic, interests and commerce transactions.
Finally, timeliness is all about how quickly the data is captured and becomes actionable. For example, capturing a cart abandonment within a few minutes could be extremely valuable to ensure the consumer is put into the appropriate segment to receive additional discounts to complete the purchase transaction.
While data is the main ingredient for creating effective audience segments, having the right analysis, visualization and reporting tools makes a huge difference, especially when deals with very large volumes of data.
In my next post I will discuss a range of tools designed specifically for customer-centric analysis and segmentation. Until then, start identifying all different sources of relevant and timely information about your consumers.