Bringing offline data, such as in-store transactions, online, a process called onboarding, is a hot trend creating new opportunities for optimizing ads and attribution to prove the return on investment for business actions. A report released by Nielsen Catalina revealed that enterprises across industries on average tripled the ROI by using more optimized ads. This finding points to the advantages that enterprises can gain by unifying online and offline data sources.
As a result, investors are pouring money into technology enablers that make offline data more easily accessible. Notable transactions in the online-offline space include:
- DataLogix raised $45mm in June 2014 and recently acquired shopper marketing firm Spire, enabling them to match offline purchasing behavior data to an individual’s browsing cookies, to then send to Facebook and Twitter allowing them to sell hyper-individualized ad segments to target people who bought specific products, like Kraft Mac and Cheese.
- Dunnhumby, the loyalty analytics provider, acquired Sociomantic Labs for over $150mm in March 2014. The firm specialized in programmatic advertising for targeted online ads.
- Acxiom acquired LiveRamp for $310mm, a platform that securely onboards offline data and creates a single ID for a consumer, that other technologies can then run ads against.
- Google acquired Adometry, an online attribution firm, enabling the company to link consumer actions to online ads, bettering the measurement of their impact.
THE VALUE OF ONBOARDING OFFLINE DATA
The value of onboarding offline data comes from bridging the gap between what we know about consumers online and what we know about them offline. Offline data, such as point-of-sale transactions, weather, in-store traffic, and segmentation data (age, lifestyle, income, etc) can often times be more valuable than data retrieved online because it is the result of direct interactions with consumers, versus indirect sources like via social media or browsing cookies. In addition, closing the loop between a purchases and the marketing source has considerable value when compared to other engagement metrics. This ability, which has traditionally eluded marketers, is now becoming available. Even search leader Google is working on ways to connect offline.
More personalized, contextually relevant advertising efforts are essential in a world where consumers are bombarded with ads and channels to purchase products from. For example, via John Doe’s purchase history we know that he often buys black bean burgers and never buys meat products. Possible product attributes of a black bean burger may be burger, but more specifically could be vegan. From this information, an advertiser can programmatically create ad products that are more relevant to him, featuring other vegetarian products he might want to try. Another option would be to explore frequently purchased items (affinities) to black bean burgers, like brands of rice or fries, to determine what coupons would return the greatest ROI when marketed to him.