What Does a Prescriptive Attribution Solution Look Like?
by Egan Montgomery, on January 28, 2018
Want to know what powers a Prescriptive Attribution solution like DemandJump has?
It all comes down to the science of networks. In the case of marketing, this network is the flow of users (customers) between massive networks of web domains (sources) over time. Once constructed, the network becomes a map for marketers, directing them to the most powerful sources of qualified traffic and revenue in their unique ecosystem.
Constructing this map takes sophisticated mathematics, data processing and artificial intelligence. At its highest level, however, we take a company’s own cross-channel data. Traffic Cloud™ then overlays market intelligence, collected from our proprietary web crawlers, 3rd party data sources, etc.
We then apply different forms of math to the right problems to deliver Prescriptive Analytics and ultimately Prescriptive Attribution. The end result? A marketer can show up to work every day with a clear plan of action with predictable forecasts and results.
There are several advantages that come out of solving for attribution in such a way.
- Data Collection and Centralization: DemandJump was built to connect disparate data sources into a single platform. It’s not possible to solve for attribution in silos. The power of the network lies in the relationship between sources over time. Social influences search, which influences content marketing, which influences PR, and so on. DemandJump integrates all your data in one place to construct a complete model of your digital ecosystem.
- Unbiased, Transparent Data: We mentioned “Goliath’s Bias” above. DemandJump is completely independent of any sell-side advertising platforms. We have no incentive to mask the truth from our customers. Transparency is in our DNA, so our customers know they are always seeing one thing… the truth.
- Side-by-Side Analysis: See all your data, any way you want it. Including side-by-side prescriptive attribution models.
- Algorithmic Attribution: Rather than shoehorn all customer interactions into an error-prone linear model, we view attribution as a Bayesian network of interactions between channels. Taking this view of the world allows us to account for all possible interactions a consumer has with a brand without having to sacrifice statistical
rigorin order to solve the problem that really matters… optimal allocation of marketing spendacross channels.
- Unsupervised Machine Learning: DemandJump’s algorithms are always getting smarter. The more good data we collect, the stronger the insights become.
With the proper techniques and implementation, Prescriptive Attribution is not only possible - it’s available now. This type of technology signifies the next great wave of marketing, which could result in the reallocation of billions of dollars in digital spend.
What light would be shed on this industry if marketers could rely on a truly independent Prescriptive Attribution and analytics solution, complete with robust data integration and centralization capabilities, endlessly customizable dashboards, cutting-edge mathematics and AI, and accurate integration of a brand’s owned data with market intelligence?
Marketers would have, for the very first time, a centralized source of the truth. A marketing brain.