Photos: Nike
Will tech acquisitions enable Nike to drive personalization at scale?
On its third-quarter conference call last week, Nike Inc. expounded on its recent acquisition of Datalogue, a data integration platform, and its overall push to tap insights that it can use to drive personalization at scale.
Datalogue’s machine learning technology automates data preparation and promises to help Nike integrate and access data from all sources — including its app ecosystem, supply chain and enterprise data — in real time.
John Donahoe, president and CEO, told analysts that Datalogue represents the company’s fourth data and analytics acquisition over the past couple of years. Others include consumer data analytics firm Zodiac in 2018 and both computer vision company Invertex and predictive analytics company Celect in 2019.
Mr. Donahoe said the “most obvious place” where data is expected to help are in customer-facing situations, such as more personalized search and recommendations. He said, “Even in this quarter we saw use of data deliver more targeted communications to consumers and more personalized experiences. And I would say, relative to what’s possible, we’re just scratching the surface there.”
The second area is “getting the right product in the right place at the right time.” Mr. Donahoe said the Celect acquisition in particular enabled Nike to “impressively pivot” to a more direct-to-consumer supply chain. He said, “What that’s all about is knowing what inventory we have present in local, regional warehouses so that you can get it delivered more rapidly.”
Third, Nike can utilize data to create better products. As part of its organizational realignment last year, the brand placed data teams alongside creative. He said, “Nike has always married the art and science of product creation. And the move toward deeper and more dynamic insights, along with our talent and investments in data science and machine learning, creates a capacity that no other brand has.”
Overall, Nike’s scale is seen as a driver to unlocking data.
“Scale matters because you get the most actionable data. It’s true in the technology industry. It’s also true, I think, in our industry,” said Mr. Donahoe. “So we’ll have a scale advantage in data and it will drive both better consumer experience and efficiency.”
Discussion Questions
DISCUSSION QUESTIONS: How do you see Nike benefiting from enhanced customer analytics via its recent acquisitions? In what ways does scale provide an advantage in data optimization?
Poll
BrainTrust
Christine Russo
Principal, Retail Creative and Consulting Agency
Yogesh Kulkarni
Chief Operating Officer, Antuit.ai
The more data and insights you have, the better you can truly understand your customers’ needs, wants and preferences. Data silos for omnichannel retailers have been an ongoing barrier to attaining a 360 degree view of customer data. Nike’s recent technology acquisitions offers it ultimate control of custom development to gain the most benefits from these applications. In addition to improved customer intelligence, Nike will have enhanced agility to respond to shifts in customer demand and supply chain disruptions.
Where I’d like to see it used by Nike is to start to prescribe improvements for me as a runner, mountain biker and swimmer. My Garmin Fenix does a pretty nice job of telling me past performance and making light suggestions. My Apple Watch also keeps nice records and helps with basic daily prompts. There is so much space in more detailed prescriptions for people. Nike has some gaps because people don’t always wear shoes, but they have a habit of wearing watches. So IMO they can keep cranking out cool lifestyle shoes but to own fitness will be an uphill battle, maybe they stick to fashion and performance footwear and work on on-demand footwear, etc.
Scale can provide an advantage because they have a huge customer base and existing data sets (not as many as Amazon or Apple though). In my humble opinion, if they don’t use it to add value to daily life beyond footwear then their days are numbered (don’t get me wrong, I am a fan. I typed this while wearing my comfy Nike LeBron Witness IVs).
The challenge with brands or retailers buying tech companies as compared to tech solutions is what I call institution creep. The formerly independent coders and systems analysts become beholden solely to the new owners and exchange that vibrant, innovative spirit for a 9-5 “doing it for the boss” attitude. The best people leave for other start-ups and pretty soon the brand or retailer is left with a million lines of code and a team that is a shadow of its former self. There are exceptions, of course, but we see this consistently in tech takeovers of other tech companies and it’s become just as common for non-tech companies.
Nike has made some brilliant acquisitions and Datalogue is the newest. By pursuing this avenue Nike has acquired strategic advantage and taken competitors out of the picture. Their acquisition of Celect was perfect. A system that optimizes online deliveries using 21st century math when the competition is leveraging solutions with algorithms created in the 19th century. These acquisitions position Nike to battle Amazon in the direct-to-consumer market and allows them to disintermediate them as Amazon is simply the middle man.
As we opined on previous dialogues, the challenge with data is not the data itself but the willingness for the retailer to follow the insights the data provides. It does not appear that Nike will have that problem.
I was not aware of the previous data-oriented acquisitions they made, but I am surely impressed with their outlook and attitude. The answers to running a better business that every retailer wants are in the data. The challenge is how to not get hung up in reading the mish-mash of data points but to have a system that digests the data and presents it in a understandable and graphic way.
Certainly scale, meaning resources, allows Nike to go down this path. But that doesn’t mean smaller retailers are left out in the cold. In fact once their system is fully integrated, Nike could license it out to other retailers, which would be a very profitable play as handling data is fully scalable.
Managing information using machine learning allows the direct to consumer interface that Nike is pushing towards to become more efficient, more profitable, and easier to implement within all of Nike’s other systems. More data, better use, and expanded reach of this data can only benefit Nike as they grow their products, better manage their logistics, and better define their reach to the consumer.
This strikes me as an odd question. If you’re small, the owner/operator and even store managers can gather data through conversations and engagement with customers. Analytics to me, basically, are the most recent (and likely best) way to get the economies of scale coupled with the intuitive customer-centricity of the very small.
In other words, scale begets the need for sophisticated analytics, not vice versa. The interesting space for me is the mid-market retailer, who can’t afford data scientists and have grown big for the intuitive customer-centricity of the small retailer. This is where vendors must step in and help the retailer.
Nike have been very shrewd. They have made some very smart acquisitions in order to be able to not only find out what people are doing but extract value from the data by using it. They are not alone in this – Under Armour appear to be making similar moves. However given Nike’s wider range this could give them the edge. Moving more toward a direct-to-customer model will also aid things as it means they can own more of the data across the entire customer lifecycle.
Nike will see the fruits of this data and information in spades – and in their numbers – in a year or so. It will be rocket fuel. The immediate concern is their supply chain, as their stock was hammered because of issues. As they simultaneously build out the “front end” using data (meaning connections to consumers) they will need to (and they are) build out the back end. Seeing how they resolve the supply chain will be fascinating to watch.
Absolutely, Christine. I find even in our discussions about data we tend to silo their reason for being. It is not understanding the customer, it is not personalization. It is not product development. It is not supply chain. It is all of them and more wrapped together.
Nike has already been a leader in the area of personalization. They have been a case study on how to create a loyalty program that is more about personalized information than it is about anything else. Nike customers feel connected. They feel as if the company knows them through promotions, personalized content, recommendations and more. This acquisition just ups their game to a higher level.
True personalization could only be empowered by a steady and significant data- and analytics-first approach. As long as brands such as Nike are staying true to their brand promise, and providing the level of personalization and the overall value their loyal customers are seeking, then people will be more than happy to share their personal data.
Nike has taken the necessary steps to achieve personalization at scale by taking ownership of their brand, consolidating their distribution strategies, taking further control of their branding/digital marketing, driving outstanding in-store experiences, and enhancing their strong relationships with their customers. Their digital transformation has enabled Nike to respond, react and proactively shift its strategies to the increasingly complex consumer landscape.
This is a teachable moment to remember Under Armour’s acquisition of My Fitness Pal, arguably the largest longitudinal database on food and weight and nutrition at the time. UA could not leverage this the way it should have. Then we have the example of Nokia buying Withings — which, in a matter of months, was taken back by some of the original Withings founders and is back online stronger than ever. Nike must become a tech/health company and ensure its staff have the ethos of tech and well-being — and learn from other companies’ missteps. It is the right strategy … now, to execute.
Many retailers are drowning in data. A robust customer analytics platform is one thing, but being able to share and digest data across departmental silos is another. And by that, I mean making data actionable, another recognizable bottleneck. So yes, data optimization (Always Be Optimizing) is so important to first scale data and make it actionable for omnichannel initiatives. Datalogue is going to be great for Nike by providing real-time solutions for product creation and insights. As long as retailers can stay within data protection laws, then I see data optimization as the only way forward, especially as we have more people shopping online than ever before.
There’s no question that Nike has the potential to realize enormous benefit from its data through its acquisition and other resource commitments to doing so. Given their recent quarter, there’s also clearly a critical need to do so.
However as an avid runner (and cyclist) who has shared running data with Nike, regularly purchased running shoes have been part of what is now called “membership” for years, and I’m still waiting on the better and more relevant member experience.
Thus I’m not as bullish on the outcome as I am on Nike’s possibilities. Others in the category are not only gaining ground, but in some cases they are ahead.
No two feet are the same, even one’s own two feet differ from each other. Yet, most examples of the personalization of shoes are only aesthetic in nature. As a global brand, the biggest opportunity for Nike is driving functional personalization using the power of data and analytics.
Two examples come to mind.
At Road Runner Sports, they did my 3D foot scan by having me walk on a treadmill for 5 minutes and recommended my perfect-fitting shoe size and custom-made sole for each foot. I don’t ever remember happily spending $150 for a pair of shoes before. It’s not yet 12 months since I purchased, but I am eager to see if they reach out to me with an offer soon to drive another sale.
One more interesting example of personalization I have heard about is from On-Running. At their NY flagship store, they have their stores fitted with cameras and sensors that accomplish the same objective as Road Runner but without one having to get on a treadmill. All you need is to be yourself in their store. Planning to visit them next week.
Nike has changed the way it brings insights into product development and design, where they have a single source of truth when it comes to data, and the insights gathered will now be used through a centralized insights team.
This is new territory for Nike — they are inherently used to working in silos.
Part of Nike’s digital transformation was taking control of their customer data and using it at the start of concept, before product creation thus getting closer to customers. Nike will not only benefit from enhanced customer analytics but now that they have reorganized the way they work, these analytics can actually be used much more effectively.
Data will sit next to product creation across categories and one set of insights will be used across product verticals which means the messaging will be consistent.
TL;DR – Yes, Nike is making meaningful strides towards personalization at scale using data.
True DTC model is all about knowing everything about the customer and serving the customer uniquely. Nike has to know everything about the athlete — not just what they buy, but also what drives their motivation to buy. As an example, through their NRC and NTC apps, Nike knows how much mileage I am running every week, so they can recommend a shoe to me every 3 months like my barber recommends a haircut every 4 weeks. They know my running speed and calories burnt, so they can cross and upsell their innovative products that have better running stability.
Personalization isn’t just about recommending products, but it is about “mass individualization” for them too — just as you order your own cup of Starbucks coffee. Nike is culturally changing from being a great consumer brand to a great digitally enabled brand. I applaud them for making the right moves with the tech acquisitions.
The use of data to personalize products and communication (“getting the right product in the right place at the right time”) seems to create an obvious path towards direct-to-consumer, therefore bypassing 3rd-party retailers. And indeed Nike has been slashing the number of stores that sell their goods. But Nike alone can only get so much information about their customers. I wonder whether smart retailers could partner with Nike not just to sell their shoes but also, based on their wider relationship with their customers, to help enrich Nike’s data and put it into a broader context — therefore making them indispensable in Nike’s data-driven strategy.
Nike’s recent acquisitions serve to leverage the company’s expansive customer base as a source of important data that will ultimately create a more personalized retail experience. The brand’s scale enables more rapid data-based decision-making and product development that empowers Nike to provide the value their customers are looking for and ultimately strengthen their brand relationship with consumers.