“Do better” - Your First-Party Data Users
First-party data runs our mar-tech and ad-tech industry. The top media and retailer companies are also the top first-party data companies. Those without good first-party data are dependent on those that do. Mastering the value exchange and earning trust with your customers, shoppers, and users has never been more important.
So why do we still stink at it then? We can do better. Way better. And by ‘we’, I mean the industry as a whole, including the device and media platforms that most of us must communicate through.
So why the rant? Thanks for asking. In the past week or so, I have had several personal examples that embarrass me as an industry veteran. Below are a few real examples of how I was recently asked for my data (some creative freedom and snark added for effect).
“I know you said no before, but do you mind if I track your every movement 24x7? We would tell you why, but no.”
“I know you are in a hurry, but do you mind approving this 7-page agreement before I get you the discount I promised?”
“I know we just met, but could you tell me how much money you make?”
“Sorry to butt in on your app experience, but can you give me your mobile phone number too? This will help us secure the data you already gave us last year, among other things.”
Okay, how stupid do you think we are? And if we are that ignorant or gullible, it is not cool to exploit us.
Trust me, I know why we historically avoided or blurred our intentions as marketers. I think it is time to change. Not because the government is making us, but because it is the right thing to do. A winning thing to do. We need to find some middle ground between our device platform’s scary ‘Do you want to be tracked across the interest? YES or NO?’ and five pages of legalese between you and the latest NFL draft gossip. Consumers are getting more savvy and are increasingly ready to trade their data and time for our discounts, content, convenience, and perks. Let’s figure this out, together.
<rant over>
Despite numerous bad examples like the above, I have been a part of some successful ‘data for value’ barter agreements. Retailer Shopper Loyalty programs, for example. It is not always perfect, but shoppers knowingly exchange their data for discounts. The streaming media industry’s shift back toward ad-supported subscriptions is also helping reinforce a similar value exchange. Overall, meh.
So how do we get better? Of course, I do not have all the answers. I can however share some thoughts and approaches that I think may help. I am going to steer clear of overly geeky advice and focus mostly on the business considerations between you and your customers. So sorry, no advice this time on CDPs, composable CDPs, decomposable CDPs, CRM, DMP, MDP, or any other combinations of your C, D, P, M, or R Scrabble letters.
Let’s start. The first step is to align cross-functionally on business objectives. What outcomes are you willing to invest in, basically? First-party data benefits are near endless, but so are the costs and commitments you will be making to customers and your business. Everyone needs to be aligned. Examples of business objectives include:
Retaining and growing current customers
Acquiring new customers
Improving your marketing effectiveness (via behavioral targeting, personalization, trained models, etc.)
Positioning your brand better with retailer partners
Understanding your customers better
Understanding your product better
Understanding your competitors better
Informing your AI and ML models
Saving money over other investments (e.g. 3rd party audiences, purchase panels, surveys, etc.)
Now for the gut check. Ask yourself how much you are willing to pay for each of these objectives. Many objectives have unique data and usage rights requirements that have incremental costs, some considerable. For example, if customer acquisition or broad market insights is your objective, you likely will need to bump up your recruiting and incentive costs to make sure your data is not biased toward your loyal customers or deal seekers and are confidentially representative of the broader market and customers you do not have today.
Lastly, do an objective reality check. You should honestly assess your current and potential relationship with your customers. At least for the first few iterations of your first-party data journey. Be creative, yet realistic. Retailers and media companies have an inherent advantage as people need to interact with them to survive and be entertained virtually every day. Conversely, how many people wake up and think about their ‘relationship’ with their favorite breakfast cereal? Yet, as a kid, I read my cereal box cover to cover. I got free samples and coupons from brands directly. I cashed in points for free music, clothes, and chances to win! Dream big, but pace yourself.
With realistic objectives in mind, you need to determine what specific data and usage rights you require. This will vary by vertical, but first-party data tends to fall into the following groups:
Data that tells you about them (e.g. name, demographics, preferences, attitudes, etc.)
Data that helps you reach them (e.g. postal address, email, phone, IP address, mobile ad id, etc.)
Data that chronicles their behavior with you (e.g. purchase history, website visits, likes, comments, customer service interactions, etc.)
Data that provides visibility into behavior you cannot see (e.g. survey feedback, competitor receipts, polls, wish lists, etc.)
There is also ‘enriched’ first-party data that is acquired via third parties that augment your own knowledge. This often includes demographics, digital activation ids, lifestyle segmentations, etc. The key consideration here is to make sure that your data augmentation partner shares your data ethics and that you stay consistent with your own customer commitments regardless of the data’s source. For example, in my personal rant above, the app that I previously told could only track my location while I was using the app somehow still knew my location enough to ask if they could know my new location more officially. And yes, I was not using the app at the time. I checked. Twice.
Now that you know what data you want and why, you need to be prepared to make a clear and compelling case. What are you prepared to offer for their data and time? The days of not overtly asking for customer data are over. There is more self-awareness, more customer awareness, and definitely more government awareness to guide ethical data collection and use. The FTC shined more light on its ethics stance last week in its Technology Blog. Among other things, they reinforced that context matters when asking users for data and that “Firms do not have free license to market, sell, and monetize people’s information beyond purposes to provide their requested product or service” and that “all browsing and location data are sensitive. Full stop.”
All customer barter deals consist of an offer and an ask. As for your offer, you need to determine what is fair, agreeable, and affordable. For some, simple discounts and content are enough. For others, you will need to curate an ensemble of value. Your offer will vary wildly based on your circumstances, but typical offers fall into the following categories:
Immediate monetary incentives (e.g. discounts, coupons, rebates, etc.)
Accumulative and loyalty monetary incentives (e.g. cashback, gift cards, prizes, etc.)
Services provided (e.g. free content with ads, free app, etc.)
Convenience (e.g. streamlined user experience, automated shopping list items, customized assortment, etc.)
Member perks (e.g. preferential treatment, free stuff, status, etc.)
Relevant content (e.g. personalize content, health information, recipes, etc.)
Chances to win (e.g. prizes, money, etc.)
Your ask is the tricky part. This is the part that turns people away and will put pressure on your offer, which of course is why the industry has historically buried this detail in the fine print. Make a thoughtful and fair offer. Be confident in your offer. Say it loud and proud. Most consumers know they will get ads regardless. Give them a chance to influence what ads they see. While selling the benefit of relevant ads alone is surely not enough, it can help reduce the angst that sometimes trumps your other value propositions.
One industry challenge is that our collective asks are so varied and complicated. This makes it difficult for consumers to quickly assess an increasing number of data offers. I would love it if the industry could somehow align on how to categorize and explain our data asks better. For example, could we categorize the scope of our data asks to something like the below? Your data will be used …
just for ME within the OUR SERVICES
just for ME to share information OUTSIDE OUR SERVICES
just for ME and MY RELEVANT PARTNERS within OUR SERVICES
just for ME and MY RELEVANT PARTNERS to share information OUTSIDE OUR SERVICES
for ANYONE in an ANONYMOUS fashion for a SPECIFIC USE CASE
for ANYONE in an ANONYMOUS fashion for ANYTHING legal and ethical
Once you get everything in place and you are successfully collecting data, earning trust, and accomplishing your objectives, know that you are not done. You are never done. Your first-party data will become the fuel that helps drive your entire marketing flywheel, so you cannot afford to let it get stale, lose scale, or become skewed. That means that you need to continually invest and prioritize monitoring, measuring, and fine-tuning your first-party data. Some desired objectives will not be met. If so, make adjustments where you can, and don’t be afraid to cut objectives from your first-party data scope and use the cost savings on other alternatives.
I hope this helped. I know it was fairly generic, but then again, earning customer trust and creating value is universal and the foundation of any successful first-party data strategy. Good luck. Email me at dan@harmonymartech.com if interested in discussing how I could help your first-party strategy.