I often struggle with the term personalization. It’s not because I struggle to comprehend the definition, but rather its meaning in the context of everyday business settings.
Many of us have observed or experienced personalization fails. The most common in my life is purchasing something online, then being stalked by an ad for that very thing for a couple of weeks following the purchase.
Me: cool seal… *like*
The algorithm: pic.twitter.com/maHhI4kBn3
— R/GA (@RGA) April 2, 2018
Although this isn’t what we desire when we refer to personalization, it is for the most part the reality of today; a series of inferences based on an incomplete profile of us.
On the flip side, these inferences can work really well. In fact, businesses that engage in efforts to personalize tend to perform better financially.
The problem is that all personalization efforts are based on a very incomplete, often inaccurate set of data. No one company knows everything about the human being they serve as a customer.
Because of this I’ve always wondered what we’re aiming for. What is our actual objective when we throw out the word personalize? What are we trying to achieve and how can we frame this objective in such a way it becomes more meaningful and actionable?
“All personalization efforts are based on a very incomplete, often inaccurate set of data.”
I’ve framed the opinion, after many discussions and some subtle contextual inquiry, that our intent to personalize is driven by a deep desire to increase the likelihood a person is compelled by our value proposition. So compelled they actually do something, like sign up, buy, or recommend. After all, these outcomes define our success. These are the outcomes we’re optimizing for.
At Greater Than X, we call this designing for situational relevance. What we mean by this is a value proposition meets a need, solves a problem, or fulfills a job to be done at the time it’s actually relevant. Achieving situational relevance means clearly defining constraints. It means knowing what you don’t do, what problems you don’t solve, and what jobs you leave to other providers. It also means deeply knowing your customer, something that is much harder to do than it is to say.
This article is about introducing you to situational relevance, what it means, and the steps you can take to start designing for it.
What it means to be situationally relevant
I’m not the first to talk about a concept like situational relevance. In fact, a recent report from Accenture refers to a term they’ve dubbed hyper relevance. Without getting too semantic, the primary difference between situational and hyper relevance is that the former focuses a brand on specific situations people find themselves in, while the latter requires an “always on” mentality. The outcome for the customer may be very similar—a product or service that relieves a pain or creates a gain when they need it most. However, there are stark differences between brands focused on specific things and brands focused on everything.
In the report, the authors recommend organizations do three things to make hyper relevance a reality for their brand and customers:
1. Look beyond the traditional customer journey
Companies that distinguish themselves with hyper-relevant experiences look beyond the traditional customer journey. They identify and prioritize those areas where hyper relevance can deliver added value and quickly address the unexpected. What can we offer once we realize our customer has missed their flight? Received a job promotion? Been forced to flee a hurricane? In these situations, customers need different things and relevance becomes supremely important.
2. Rethink data
Hyper-relevant companies don’t rely solely on descriptive analytics or traditional sources of information. They invest in predictive analytics, collaborate with an ecosystem of stakeholders to capture real-time snapshots of every consumer, and mine data in new ways to understand the customer journey that extends beyond core products and services and across channels.
Related: The data trust gap and how to close it
In addition, hyper-relevant companies redouble their data security efforts. They ensure customers have full control of their data across touchpoints. They eliminate duplicate requests for customer information and permissions. And they make sure all customer data is secure and visible to employees on a need-to-know basis.
3. Earn trust continuously
Trust must be a key consideration when designing hyper-relevant experiences, creating new customer value propositions, and serving as a critical resource when customers need them most. A company’s commitment to delivering the experiences that were promised and meeting customers’ expectations is paramount.
Hyper-relevant companies understand their baseline level of trust, and eliminate issues or irrelevant offers that detract from the trust quotient. They make trust sustainable by establishing a rigorous process and a robust, cross-functional governance structure to continuously measure trust and hyper-relevant effectiveness—and act on their findings. Most importantly, they manage trust as the critical growth enabler it is.
In theory, these three areas of focus set an organization on the pathway towards something like situational relevance, or as Accenture puts it, hyper relevance. Although the report and its recommendation are solid, I’d like to again propose a different point of view—something that’s been working within our client projects.
Designing for situational relevance
When we think about situational relevance, the first thing that comes to mind is clarity, the second is proximity, and the third is the outcome. Together these three focus areas enable us to do practical work that moves the needle towards situationally relevant propositions.
Here’s what we do:
Step 1: Start by defining a strong point of view
Brands that lack clarity also lack meaning. To earn people’s trust and eventually gain access to a deeply relevant view of their life, you’re going to need to get very clear on what you do and what don’t do.
How you achieve this point of view will depend on your approach to customer research, market intelligence, and ecosystem mapping. However, the outcome you’re looking for is a defined set of customer jobs or situational contexts in which your brand is best placed to deliver the outcome people seek—or, better yet, the outcome they’re yet to discover. Once you’ve defined this you can start designing your organization to most effectively enable those outcomes.
“Brands that lack clarity also lack meaning.”
Step 2: Conduct a trust audit. Then take action immediately
From my experience I’ve learned many organizations have no idea how trustworthy they are. They aren’t sure why people choose to do business with them. They’re often quick to make assumptions about why people share their data. They rely on limiting metrics like NPS—assuming a high score equals high trust.
What’s worse is they don’t really know what parts of their business earn or erode trust. Without this view of your current state it’s going to be hard to practically execute any strategy that leads you to become an inherently trustworthy brand—a brand that earns access to a view of your customers’ life that very few other brands have.
For too long trust has resided at the edge, or perhaps even the outskirts, of organizations. It’s remained an ambiguous concept to most. It doesn’t have to be, though.Trust can be demystified. Different aspects of trust can be quantified. Trust can become a competitive advantage and lead you towards situational relevance.
For more on trust mapping, I suggest reading the first and second installment of this two-part series from the Center of the Future of Work.
Step 3: Make data meaningful
You aren’t going to get to know your customers better than any other brand by physically following them around. That’s both costly and creepy. You’ll gain this view by earning access to the life data that’s appropriate to your point of view—the clearly defined customer jobs you’re uniquely positioned to fulfil.
To earn this access you’re going to have to put the customer at the center of their very own data ecosystem. You’ll need to embed market-leading customer identity and access management capabilities. You’ll need to evolve your design principles, patterns, and practices so that people share more while remaining in full control. Just because they shared today doesn’t mean they’ll want you to have access tomorrow.
Lastly, you’re going to need to make data trust part of your value proposition. You need to be radically transparent. You need to deliver the value you’ve promised you will. You need to own the consequences of your actions, whether positive or negative. You need to be a proactive, reliable, and, above all, an inherently trustworthy custodian of customer data.
If you achieve this status as a trusted custodian of people’s data it will mean you’ll gain access to the right data just when you need it most. When it comes to situational relevance, this is the thing that matters most. Perhaps the best examples of this can be seen in the personal information management services market. Although there are a number of noteworthy examples, Digi.me’s work with the Icelandic Government is among the most high profile.
“You need to be a proactive, reliable, and, above all, an inherently trustworthy custodian of customer data.”
So let’s say we do this. Let’s say we define our point of view with exceptional clarity, we get to know our customers unlike any other brand, and we design our organization in such a way we can genuinely be trusted to process people’s data and deliver superior outcomes. What comes next? What future are we actually designing?
The future isn’t personalized, it’s personal
Situational relevance is something we can strive for now. If people trust us with their data, we can deliver outcomes to the right people at the time they need them most. This is exciting, as there are few examples of this happening today. But situational relevance as we define it at Greater Than X probably isn’t ambitious enough for the longer term.
I envision a future where technology doesn’t simply augment our abilities—it works directly for us. I really mean you and me individually. I’m not alone in this vision either. Personal AI is a hot topic.
The difference between personalized technologies and personal technologies is who they work for. Alexa, regardless of how sophisticated it may eventually become, will always work for Amazon. It may one day become an effective personalized technology. It’ll never become a personal technology.
And that’s perhaps the bigger question you need to ask: Are you working towards a proposition that is personalized or personal? What you design today and how you approach that practice will impact this future. It’s likely there will be plenty of room for both.
I’ll leave it up to you to decide what the future holds.
by Nathan Kinch
I'm the founding partner of >X , a research, design and strategy agency at the forefront of the personal data economy.