My Inbound 2019 session – The new frontier of brand management: ethical approaches to consumer data.
By Stephani Estes, SVP Executive Director of Media
Earlier this month, I attended and spoke at the INBOUND 2019 conference in Boston. It was four days filled with a lot of talk about using data for personalization. That made it a great place to talk about a new frontier in brand management – ethical data management. If I missed you in Boston, here’s a recap of what I shared.
It’s been (over)said that we’re in the age of “big data.” Having access to consumer data has created a lot of new marketing opportunities but it’s also created new considerations for brand management. A critical part of managing a modern brand is having an ethical approach to consumer data.
Why does consumer data matter so much?
It’s all about experiences. Modern brands aren’t defined by iconic logos or well-produced ads. They’re defined by the experience they deliver. And, to deliver a better experience, you need better data. Consumer data is a proxy for a relationship. It fills in the gaps and helps facilitate experiences.
So it’s no surprise that consumer data can improve marketing. Marketers who have access to consumer data report the benefits: 65% saw improved consumer insights and 53% had improved marketing efficiency.1 But, there’s a downside too. The US has the highest average cost of a data breach in the world at nearly $8 million. Even greater than the monetary cost is the loss of trust that comes with mismanaging data because, make no mistake, no matter who’s at fault, consumers will blame the brand.
The law is starting to catch up on this with GDPR and CCPA but there’s still a significant amount of gray area with both of these policies. It’s been brilliantly said that “ethics begin where the law ends” so let’s start right here.
Five principles of ethical data management that can help you do right by your brand:
1. Don’t be creepy.
Yes, there are some data privacy horror stories out there – remember when Target outed a pregnant teen to her dad via direct mail? But let’s not set the bar that low. The ability to “follow” a user across the internet or incorporate their search data into messaging can indeed open the doors to greater relevance. But remember – there’s a fine line between relevance and eerily uncanniness.
How do we stay on the right side of that line? By focusing on the experience. Disney Parks has this down to a science with their MagicBand. If you’re not familiar with MagicBand, it lives up to the name – you can use it to access the park, to make payments on premise, to provide you with the perfect photo of your kids with their favorite Disney character (a must for any parent who doesn’t want to spend the trip looking through a camera lens). It will even provide a customized greeting for you at the restaurant where you booked dinner. The MagicBand delivers the signature magical Disney experience. Yes, it collects data – but it’s how they use that data that matters.
To do this right, you need to practice empathy with your data collection and usage. And remember the wise words of Jeff Goldblum from Jurassic Park: “Your scientists were so preoccupied with whether or not they could, they didn’t stop to think if they should.
2. Commit to transparency.
This often requires a mindset shift internally – the best way to get there is to assume everything you’re doing will be seen. And transparency has real implications for your business. Consumers want transparency – 94% of them will be loyal to a company that provides complete transparency. 73% are willing to pay more for that transparency.2
But if the carrot isn’t enough, consider the stick. If you think it’s going to land your brand in the headlines for all the wrong reasons, don’t do it. Once you lose a consumer’s trust, the price of getting it back will far surpass the costs that might be associated with being more transparent.
Assemble your team internally, determine your data policies and commit to being open about those policies. It’s not going to look exactly the same for every business, so figure out what’s right and true to your brand. It’s easier said than done, but it’s worth the time.
3. Educate your users (and your executives).
Once you have alignment on your plan, it’s not enough to hide it in 2pt font somewhere deep, deep in the recesses of the disclosures on your site (but do make sure you have it in your disclosures – and review it annually!). You need to initiate the conversation with your consumers. A lot of brands are anxious about doing this, but keep in mind principle #2: you’re giving consumers the transparency they want. Communicate the mutual value of sharing data. Give them a clear opt out or opt in. Explain the value exchange or loss of that decision.
Data usage isn’t going away. When the relationship is really clear (think Amazon or Zappos), most consumers are open to sharing their data. It’s when the relationship isn’t as clear that it’s imperative to build that visibility.
4. Focus on what the data reflects, not the data itself.
As I said earlier, data is a proxy for a relationship. It’s an abstraction of the complexity of reality. What isn’t there is often as important as what is there. Just because you don’t have the data doesn’t mean it doesn’t matter – just because you can’t see germs doesn’t mean that you won’t get sick.
It’s important to remember that by itself, data is imperfect. Last-touch attribution is evidence of that. Sure, it gives you directional information on consumer behavior, and for some categories (like app downloads), that information is probably pretty accurate. But for brands in a high-consideration category (say, finance), relying on last-touch attribution data alone can result in a distorted image of reality. Those short-term metrics can blur the perceived power of a brand.
What’s more – even the big guys can get it wrong. Check out your “interests” as defined by Instagram (here’s how you can find them) and see how close or off they are.
When you’re digging into the data, don’t leave your intuition at the door. Find the data sources, structures, and usage that reflect how humans actually behave. As a brand manager or marketer, you’re probably not the person doing the complex statistical analyses – but you should help inform them. Check the answers against reality and watch out for biases. Yes, we should let the data lead, but apply some common sense. And, make sure you speak the language. Take a stats course and brush up on your skills. You need to be conversant in stats to use them correctly.
5. Apply a cultural filter.
Data is amoral. It can be used for good (like improving hurricane path prediction) or bad (like the junk science of phrenology). Facebook learned this lesson the hard way with demographic and income data being used in discriminatory ways for housing ads. When you’re using data, it’s critical to apply a cultural filter.
We need this filter because data is inherently backwards facing. Even when used for predictions, it still carries the biases from the past. Consider artificial intelligence. It’s tempting to assume that the data in AI eliminates any subjectivity. But, recent uses for AI across sectors have demonstrated that implicit bias persists. From reinforcing racism and sexism in hiring or loan applications, to the widely publicized issue Google has in recognizing black faces (which still persists) – the reality is, we often just hard code our biases in those algorithms.
So, what can you do tomorrow?
Focus your data scientists on the risk, not just the reward:
- Know what you need to avoid
- Imagine the bias in the data
- Have humans check the work
Establish a new marketing sub-group, consisting of:
- Project Management
Most importantly, make sure you get this group together before you have a problem.
The brave new world of brand management through data management is upon us. By approaching consumer data in an ethical way, you can not only help protect your brand, but you can develop better, more profitable relationships with your customers.