Is there truth behind the statement that we’re all drowning in data? Perhaps. However, few marketers or ad agencies would claim they’re drowning in actionable insights. Even fewer would argue that their first and third party data insights have led to an overwhelming excess of banner advertisement conversions, because their insights are so remarkably fresh and accurate.
Gartner reports that sales via a data management platform (DMP) or data exchange (DXP) is the third most-common driver of revenue for marketing organizations. Despite the increasing prevalence of data purchase, Yesmail and Gleanster have found that 80% of consumer-facing companies lack an understanding of their clients beyond basic demographics and purchase history. In many cases, linking third and first-party (self-collected) insights within a DMP environment can lead to mixed results. Programmers have long used the term garbage in, garbage out (GIGO) to describe the results one can obtain from custom code. This concept holds remarkable truth when it comes to the results obtained from many DMP environments.
While some 36% of brands are using behavioral and attitudinal data, and 41% are using browsing history and online behavioral insights, why is there such a major gap in consumer understanding? The Yesmail report indicates that well over three quarters of marketers believe their ability to effectively segment customers is limited by their data insights. It’s clear that marketers today have data issues that aren’t necessarily related to volume of data available within their data management platforms or the volume available for purchase via traditional vendors. Their issues are likely more related to the quality and comprehensiveness of their data insights.
Data Quality Matters
In a traditional DMP environment, both first and third-party data insights may offer limited value and veracity issues. Just because a consumer was searching for a mortgage six months ago doesn’t mean they’ll convert on targeted banner ads today. If they were well-qualified for traditional home funding sources, they’ve likely received it and closed on a new residence. Additionally, just one piece of behavioral-based data on a customer isn’t enough to develop a robust understanding of customer segments. Traditional DMPs build segments based on a single piece of behavioral data. In a DXP, buyers are able to develop highly-qualified segments by merging data points. You may choose to sort targets based on a combination of qualifications and current activity. Perhaps your target is someone who is searching for a mortgage, but also meets certain income guidelines, drives a luxury vehicle, and lives in a specific region of the country.
Consumer behavior and needs change quickly, and marketers should beware data vendors who aren’t offering comprehensive data insights. Consumers may be lumped into segments based on outdated online behaviors or interests in making purchases that have long been completed. Without the ability to merge and sort based on both propensity and current activity, you’ll struggle to target the right consumers. BDEX’s data exchange platform is the first to offer truly full-spectrum data exchange. By offering a wealth of seller opportunities, buyers are able to select the right vendor offering insights within the right segments, at a price the seller and buyer determine.
Impartial Data Quality Scoring
While every third-party data vendor will claim their insights represent the best and freshest consumer knowledge available, few offer any genuinely impartial information to back up these claims. There is a necessity for impartial data scoring based on results, not the seller’s claims of recency or efficacy. Without impartial measurement, buyers may find themselves saddled with data sets that are out-of-date, or offer poor fit of consumer behavioral or attitudinal insights within segments. With the help of truly fresh insights, Clorox was recently able to unlock an entirely new series of micro targets, or sub-segments within their massive customer base. A recent case study revealed this allowed the brand to realize that their customer perception was decades out of date, which allowed total revision of their online marketing efforts.
The DXP offers a first-of-its-kind algorithm to score data based on buyer’s results. Before you make a data purchase, you’re able to track other buyer’s conversion rates based on the same seller’s offerings. In a world where both consumer behaviors and individual consumer needs can change on a day-to-day basis, being able to obtain unbiased measurement of quality is crucial. Fresh insights can yield improved targeting, conversions, and allow marketers to finally unlock genuine customer understanding.
How Else Does the DXP Differ from the DMP?
Marketing organizations utilizing the DXP can appreciate a number of additional benefits not seen in traditional DMP environments. In addition to the quality measurement and transparency features stored above, BDEX’s DMP offers the benefit of buyer and seller-controlled pricing, instead of pricing controlled entirely by the data broker.
Eight points of comparison between traditional DMP environments and the new DXP are detailed below. Buyer’s can also take advantage of unbiased, built-in tools to determine optimal purchase and selling price points to maximize their existing data resources and marketing budgets.
For an in-depth exploration of how the DXP improves upon the DMP on a features basis, check out BDEX’s recent blog, DMP 2.0 – Introduction of the DXP
image credit: r2hox via flickr/cc
