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“If you want to create a deep and meaningful relationship with the customer, you have to take really good care of them, and taking good care of them means taking good care of their data.” — Jascha Kaykas-Wolff, President, Lytics
Brands collect a seemingly incalculable amount of first-party customer data.
But as valuable as this data is, taking action on it to drive marketing, merchandising, and product innovation isn’t so simple — even with thousands of tools businesses can apply to every step of the customer journey.
Jascha Kaykas-Wolff, president at the customer data platform company Lytics, says brands haven’t been able to fully harness their data because they experience what he calls a “decision gap.” He recently shared his perspective on how brands can close this gap during a recent episode of the Unpacking the Digital Shelf podcast, "Filling the Consumer Data Decision Gap."
Here’s Kaykas-Wolff’s roadmap for how brands can use specific types of data to build even better relationships with their customers.
Several factors have made first-party data even more important.
Kaykas-Wolff says the shift to omnichannel has given brands more opportunity to sell directly to consumers, and technology has allowed them to deepen their customer relationships.
“Businesses are evolving. We all have to think about the omnichannel relationships we're establishing and building,” Kaykas-Wolff says. “In all of my engagements, the question that is consistent — from startups, manufacturers, B2B and B2C companies — pretty much every business right now is asking the question, ‘Who is my ideal customer and what are the attributes of that ideal customer?’”
Kaykas-Wolff says this question is actually difficult to answer because it forces businesses to be more discerning about the initiatives they undertake. It compels them to focus their organization on a specific type of customer and the ideal customer experience to create for this targeted segment.
All these changes are happening for brands at the same time companies like Netflix, Spotify, and Amazon have set the customer experience bar exceptionally high.
“We have seen bellwether examples of great consumer experiences that are setting a consumer expectation that consumers can get this from every single business they interact with,” Kaykas-Wolff says.
In this environment, brands must understand the capabilities they need to “create, maintain, and most importantly, deepen the relationship that they have with their customer,” Kaykas-Wolff says.
These core capabilities require businesses to make technology investments to support their people and processes, and most importantly, to organize all their customer information.
“Part of the challenge there is that the promise of just connecting together all of the attributes of a customer in a data lake didn't actually help enable a company’s processes and people to create a better experience that establishes, maintains and deepens the relationship with the customer,” Kaykas-Wolff says.
Kaykas-Wolff adds that companies have invested in several go-to-market tools to craft better customer experiences, such as customer experience (CX) and customer relationship management (CRM) tools. However, these technologies don’t solve the key problem businesses need to address, which is what Kaykas-Wolff refers to as the decision gap.
“Those capabilities are needed capabilities,” Kaykas-Wolff says about the capabilities martech tools offer, “but they don't fundamentally solve the problem businesses have to solve for when you're trying to connect together technologies, people, processes and talent. And that is really what I would call the decision gap.”
Kaykas-Wolff says businesses often have customer information sitting in a data lake and a bunch of disparate marketing tools, but they can’t easily scale their efforts.
“That decision gap — the ability to connect together that customer data into the customer experience — is where a lot of businesses are falling down. It's the area where I think more technology is going to solve the problems that this gap has exposed for businesses.” — Jascha Kaykas-Wolff, President, Lytics
It may seem counterintuitive to use more technology to address a challenge marketing technologies have perpetuated, but Kaykas-Wolff says artificial intelligence (AI) and machine learning (ML), in particular, can drive the automation necessary for brands to improve their advertising performance and customer experience.
“Utilizing AI and ML to help you make decisions at a scale we just can't achieve as humans is where this big shift is starting to happen — and that's solving the decision gap,” Kaykas-Wolff says.
Kaykas-Wolff outlined other ways brands can address the decision gap.
First and foremost, a mindset shift is crucial for brands to make better use of their customer data.
Kaykas-Wolff says brands have typically had a give-and-take relationship with customer data — customers keep giving it and brands keep taking it. He says companies have used martech tools to just suck up “as much information as they possibly could, with a hope that at some point it sat in the data lake and you could make sense of it and it would be useful.”
“That's a really bad way to build a trusted relationship — to just take everything you possibly can without somebody knowing, and then decide you're going to give something back to them at some point in time that’s going to benefit the business,” Kaykas-Wolff says.
Instead of this approach, Kaykas-Wolff says brands must always give back to consumers something of equal value to what they give to companies.
“The first thing that a consumer gives to you — without explicitly saying ‘I'm giving it to you’ — is information about what they care about by their behavioral patterns,” says Kaykas-Wolff.
Kaykas-Wolff says brands haven’t yet fully tapped into this resource and have instead focused on collecting as much customer information as possible. Lytics has run studies over the years, which found that the best way brands can give something of value back to consumers is to harness behavioral data to personalize their experience.
“You can create an amazing, personalized customer experience by just paying attention to how your customers use your first-party data, your website experience and the content you produce,” he says. “It’s not about collecting as much data as possible. It’s about focusing on the right kind of data, and that right kind of data is not intrusive. It's behavioral data first.”
Rather than deploying data to meet a predetermined set of business goals, brands need to harness behavioral data to craft an ideal customer journey. From there, they’ll see results in their business.
To create this ideal customer journey, brands need to transform their people, processes and technology to improve behavioral data collection, Kaykas-Wolff says.
“You don't have to boil the ocean. You really can start with a very focused approach. You don't have to collect all the data in the world to solve the decision gap that exists in your business.”
“Every business needs to identify the capabilities that are necessary for them to create a great customer experience. That fundamentally is going to come down to the talent you have and the processes that talent uses, and then that's going to be supported with technology.” — Jascha Kaykas-Wolff, President, Lytics
Kaykas-Wolff says brands can cultivate more first-party data by using AI-driven martech tools.
Lytics, for example, has a natural language processing engine that analyzes content across all of a brand’s content repositories, including their website and digital asset management system. The company then categorizes this content to create affinities.
Kaykas-Wolff compares this to what Netflix does to drive better content recommendations, using granular content facets or attributes about a particular TV show or movie a user watches to draw conclusions about what a user likes and what to recommend to them.
“Lytics does effectively the same thing for your business. It looks at all of the different facets and creates affinities groupings of those facets that create better recommendations based on the behavior. So, if you show up at a website and you look at product information, you move over to another piece of content that supports that product information,” Kaykas-Wolff says.
He adds that this approach to content categorization helps businesses hone in on the specific customer behaviors that drive their interactions with specific content. Using AI- and ML-driven martech tools, companies then can redeploy this behavioral data in real-time to drive better recommendations and a more personalized experience, effectively closing the decision gap.
Technology is only one part of the solution for addressing the decision gap. Cultural transformation is also necessary.
Kaykas-Wolff says companies need to prepare their teams for process automation and drive home the importance of integrating AI to make decisions at scale, assuring them the technology will be a key enabler of their work and not a replacement.
“We have to set up processes that allow for a spectrum to exist in the business so a marketer can feel they're in control of certain kinds of decisions,” Kaykas-Wolff says.
Kaykas-Wolff says companies also need to create more data-driven roles within their organizations to break through their current inertia.
“We have to be dependent upon data science, and the analyst function in particular in marketing just flat out doesn't exist in every single company — the person who understands the context of the business and is able to interpret the data that's coming from the systems we have available to us,” he says.
Kaykas-Wolff describes this role as a marketing analyst who’s solely focused on helping their company close the decision gap and developing strategies that allow the brand to effectively deploy behavioral data in its customer experiences.
Though brands already have had to transform their operations due to the pandemic, Kaykas-Wolff says they can build on this innovation to further transform their approach to data.
“What we're experimenting with is not a nice-to-have anymore, it's a requirement,” he says. “It's our responsibility as business leaders to make sure we're developing the best customer experience we can because our consumers now expect it.”
Listen to the full podcast to learn more about how brands can close the decision gap and turn their data into revenue and loyalty.