The ad tech landscape has outlived an era of turmoil marked by an overabundance of players with fragmented data solutions (buying technologies). In their wake, over-promising and under-delivering resulted in a period of confusion. As the dust finally settles, however, brands can now more clearly see whom the key players are in the platform space and make decisions about their tech stacks accordingly. Simultaneously, marketers are choosing particular buying platforms to automate media buying across search, social, display, mobile and more, and are now on the road to true automation.
Now that buying platforms have been established, marketers are asking what comes next: What data can I use to make my buying platform generate the greatest outcome to reach my marketing goals?
Recently, the IAB set out to help marketers answer this question with a new white paper. Published by the IAB Data Center of Excellence in partnership with its Data Benchmarks and Activation Committee’s Working Group, Defining the Data Stack provides marketers with hands-on information to label their data and delineate its uses.
Data’s Critical Value
We know data has emerged as one of the most powerful – if not most powerful – tools for marketers. Data connects and underpins successful engagement with consumers and provides brands with an advantage against their competition. We see this in the successes of many direct-to-consumer brands, which have achieved amazing results with limited resources.
Data delivers critical understanding about whom marketers’ audiences are, enabling them to find their best existing or potential customers, whether they’re at their desks or on the go with their mobiles in hand. In order to do this, marketers must understand what they have in terms of first-party data and determine what they may need to acquire in terms of additional data, as well as the technology to put it to its best use.
It can also turn the marketing funnel upside down, powering a customer-first approach, provided you have the technology. That way, a brand’s existing customers are the foundation upon which lookalike audiences are assembled. This more efficient strategy results in awareness that leads to interest and consideration, the triggers for intent and purchase.
As a result, data sometimes feels overwhelming. It can be hard to know where to begin and how to put data into action effectively. A good place to start is to define the data available and understand how to fill in the gaps.
Conducting a Data Assessment
To help marketers categorize their data, Defining the Data Stack provides a handy Data Assessment Matrix that organizes data into four categories: Online, High Online, Offline, Low Offline. The chart offers marketers a view into how they can deconstruct data into its most valuable properties, and apply it to meet business goals and identify areas of growth.
Case Study: Allbirds
Looking at the chart above, you’ll notice that shoe company Allbirds falls under the “High Online” quadrant of the matrix. This e-retailer knows a lot about its customers from data pulled through its CRM and site analytics. Based on the data they have, they’re able to understand how their shoppers view and engage with their content. Brands like this are in a good position to start personalizing their messaging based on who and where their customers are. With the data they were able to collect and analyze about their customers, Allbirds was able to embark on an exclusive promotion with Shake Shack. Announced via social media, the offer resonated with Gen Y and Z devotees of both brands.
Making Sense of Results
Once an organization has identified where its data fits in the Matrix, marketers can follow a series of clearly defined next steps to grow their data stacks and use data to achieve business goals.
- High Online: Marketers that collect the majority of their information from online visits and their CRM data fall into this category. If you have a solid understanding of how your customers consume your content, your next steps are:
- Think of ways to personalize messaging for your audiences, perhaps based on their climate or location
- Develop a media strategy based on where your best customers are so you can find more consumers with similar attributes
- High Offline: If you’re collecting important offline information on many of your customers today, do you feel confident about that data, or do you feel like you need to augment it with additional data to build a better understanding of your customers? Here are your next steps:
- Determine how you can connect your offline data assets to your digital marketing campaigns – in ways that are compliant for your industry and that protect your customer’s PII data.
- Find trusted partners to help you bring your data online and activate it.
- High Owned: If you are a DTC brand your priorities may center around both building awareness and growing your customer base.
- You may want to focus on your ideal customers’ overall media consumption and ensuring your brand has a strong presence in the formats and channels where you’re most likely to engage them.
- Once a sale is made, you should be relying on your CRM to increase efficiency by leaning on the modeling techniques that are already widely used in digital media.
- Low Owned: You may be among the brands that face challenges in growing your first-party data. You’re definitely not alone here.
- You’ll want to devise a plan to grow your database based on your budget and available technology resources.
- Another option is to consider developing partnerships in order to access second-party data, and then amplify the insights you discover via the acquisition of third-party data.
No matter where a marketer may be with their current data stack, there is always an opportunity for growth and better application of data to suit business needs. Armed with the understanding of their data and how it can be leveraged to improve marketing outcomes, marketers are better positioned to meet today’s challenge of reaching consumers in more meaningful and engaging ways.
Read more in Defining the Data Stack