Agile data is data that must be available in real-time and ready to adapt to the changing business environment. Flexibility is key when it comes to data ““ marketers need to anticipate change in consumer behavior and, because of that, be armed with data that can change in a moment’s notice.
As consumers traverse the web ““ via their computers, smartphones and tablets ““ they generate massive amounts of data points that reveal their attitudes, intents, brand loyalties and more. An ecosystem of data marketplaces, publishers, and data scientists are collecting, analyzing and packaging this data, and then making it available to marketers for use in their advertising campaigns. This type of data has the ability to be agile.
This trend is game-changing for marketers. Rather than relying on preconceived audiences, marketers can layer on multiple data sets to get multi-dimensional, nuanced views of their best potential customers. And they can combine first-party data with numerous third-party data sets to find highly responsive audiences at scale for their advertising campaigns.
Data ingestion is no small task; significant expertise is needed to collect, organize and segment data in all of its varied formats so that it can be made available for strategic marketing purposes.
Most importantly, marketers need to move fast ““ agility is key in a fast paced digital marketing world. The days of waiting weeks to prompt business decisions are gone ““ real time is here to stay and grow. Data has to be structured to deliver action immediately, and should shift and adapt to changing technical requirements and business conditions quickly.
Historically, advertising has been used both to impact brand loyalty and to introduce prospects into the top of the sales funnel. Our industry has devoted far too much time and effort at the bottom of the funnel, repeatedly advertising to those who have already shown purchase intent with countless impressions.
Retargeting is a case in point. One of the most common forms of audience targeting, retargeting is designed to help marketers keep their brands top-of-mind by repeatedly advertising to people who have already demonstrated some level of purchase intent. Collectively, enormous sums are spent on retargeting each year ““ 69% of digital advertisers say they will increase their audience targeting budget.
There’s no doubt that retargeting is a very useful conversion tactic, but it cannot help marketers drive new prospects into their sales funnel. Take for example a toy manufacturer that brings to market a doll designed for girls aged eight to ten. In June, the toy manufacturer may target mothers, and thanks to advances in anonymous consumer profile targeting, the manufacturer will have no trouble launching a campaign at scale. But will mothers still be the doll’s best target when the holiday season starts? Perhaps the extended family of girls aged eight to ten will prove to be the best converters, as grandparents, divorced dads, single aunts or bachelor uncles seek out the latest must-have toys. In such cases, the toy manufacturer may be wise to widen ad spend to include additional demographics ““ but which ones?
Lower-funnel marketing alone will not help the marketer increase market share or raise awareness among potential customers. Marketers need to use real-time, flexible data to keep up with their fast-paced consumers. They need to use agile data.
Achieving agile data can be done in 4 steps:
- Take a marketer’s first party data as a seed.
- Scale the audience with third party data.
- Act on that data across multiple media platforms.
- Adapt the data based on real-time feedback.
step 1: taking the marketer’s first party data as a seed
Agile data starts with understanding each advertiser’s and each campaign’s specific business goals, including campaign goals, desired scale, definition of success and the means by which it’s measured.
Once business goals have been established, it is in the marketer’s best interest to start with the consumers who have raised their hands and taken some action on a marketer’s website or mobile app that shows their interest and intent. These consumers make up the first party data and are the most likely to convert.
step 2: scale the audience by adding third party data
First-party data alone isn’t enough to scale a campaign ““ a critical point to be made. If digital marketing is to break free from lower-funnel marketing activities and concentrate on upper funnel prospects to grow market share ““ massive scale is paramount. Therefore, it is critical to leverage multiple large-scale data sets, including third-party behavioral data, user agent, and even offline data to reach millions of real-time top performers. By combining first party data with third party data, marketers can create super charged segments that help target audiences at scale. Modeled data can help reduce ad spend waste and make first party data actionable.
It’s important to note that large datasets provide more than just scale. More data enables better decision-making. Diversified data enables even better decision-making by delivering more granular insights. So while many marketers may be tempted to reduce costs and complexity by limiting datasets, the better approach is to diversify data inputs, onboard more of it, and act on the insights that will result.
Note, however, that all data are not created equally. The quality of data inputs drive the results one can expect to see. While it’s true that more data, in general, is better than less data, it is important to continuously measure the quality of data inputs. Third parties such as Nielsen and comScore can help ensure the veracity of data sets, and help avoid garbage in and garbage out.
step 3: act on the data across multiple platforms
Agile data demands flexible data delivery.
To expand data distribution and profit, delivering data across multiple media platforms is necessary. While adding third party data helps create more scale for a campaign, pushing those modeled segments across any platform ensures that more reach is achieved, and this must be done by a trusted, enterprise-level data partner that can provide reach, throughput, and reliability.
Additionally, if a demand side platform (DSP) or trading desk partner is delivering the advertiser’s campaign, an updated model must be fed to that platform just as soon as quantifiable changes are detected.
Because the top-performing customers are likely to span multiple distribution channels, agile data must be platform-agnostic, enabling the marketer to reach their optimized audience wherever they may be found within the digital ecosystem. Marketers, therefore, should seek data models that are usable on any platform, including ad exchanges, ad networks, DSPs, mobile DSPs, etc.
step 4: adapt the data based on real-time performance
In addition to flexible data delivery, data must be completely flexible in that it can change in a moment’s notice based on how consumers behave online.
Agile data requires continuous updates and revisions in the pool of user IDs to incorporate the most recent actions each user performs. This ongoing process enables better campaign performance based on real-time results. As more information is learned about a consumer, they are reevaluated and re-scored in real time, leading to the most accurate view of a consumer’s behavior. For example, going back to our earlier toy analogy, if we should happen to see a single, older males buying toys or even clothing appropriate for girls aged 8-10, we might determine in real-time that they are now ideal prospects for a doll campaign, and we could assume that they have a daughter or family member at that age who has a birthday around that specific time.
Most custom audience targeting data models can’t adapt to ongoing campaign signals. Data that is agile can help distinguish what is and isn’t working in a campaign and correct itself to better find consumers.
Once top performing consumers are identified, they become an optimized audience for a given campaign. Optimized audiences include all consumers who demonstrate a propensity to meet the campaign goals. By definition, the optimized audience will be specific to the campaign or an advertiser, and are never static or shared.
To incorporate real-time campaign learnings into the marketing process, user IDs must be scored based on their propensity to convert, and placed into distinct datasets”“ all of which are proprietary to the campaign. User IDs with the highest scores should be sent to marketing systems for targeting in real time.
For example, if a user does actions A and B, that user may be deemed ““ in real time ““ a likely converter and incorporated into a data segment that might, depending upon minimum scale requirements, be worth targeting. However, if that same user goes on to perform action C even at a later date, it may indicate the highest probability to convert. That user, therefore, will be moved into the best data segment for immediate targeting.
what eXelate does to provide agile data
At eXelate, we believe that big data needs to be harnessed to create smart, agile data that gives marketers a better understanding of the types of consumers they could ““ and should ““ be targeting. We provide data and insight on online purchase intent, household demographics and behavioral propensities that enable digital advertisers to make optimal marketing decisions. Our products help power smarter marketing decisions using data that is in real-time and is flexible
Marketers need to know what their consumers are doing, and now. The days of lengthy market research cycles and incomplete views of consumers have passed.
eXelate optiX” is the consumer insights terminal that turns all online and offline interactions into consumer insights through the power of trillions of data points. optiX gives marketers instant consumer insights available in real-time dashboards with constant syncing and visualization updates. optiX provides a comprehensive, immediate, and ready terminal for marketers to get consumer insights-as-a-service.
A top 5 insurance company was seeking to understand the profile of their consumers for various product offerings and see how their behavior varied throughout the purchase journey across different products. eXelate worked with the client to tag the path to purchase of four of their products and provide a comprehensive analysis of the profile of the consumers for each product, how their behavior varied across different products, and how their behavior varied at each stage of the purchase funnel. This analysis informed a more effective marketing strategy which led to better messaging, creative, and segmentation for our client. These were incorporated into their digital and TV strategies and revealed untapped growth opportunities and increased ROI.
A key component of agile data is its flexibility ““ the ability to adapt to changing business goals, quickly.
eXelate’s maX custom modeling scales a marketer’s seed audience to maximizing branding and direct response campaign outcomes. maX creates customized modeling through a combination of first party users and eXelate’s 800M users and delivers them via 75+ connections to media platforms for model-and-execute. These models adapt daily to campaign signals ““ up to 1M syncs per minute.
An insurance company was looking for a cost-effective and scalable custom audience to drive more acquisition. eXelate offered a solution by creating maX models that would utilize our integration with Xaxis to receive campaign data files and tailor custom audiences based on the high performing campaign responder seed data. The maX models that were created were able to drive more than 6.2x more conversions at 20% lower CPA.
It’s time for the world of digital marketing to move from being big to being smart ““ through actionable, accurate, and agile data.