Kohl's cashier scanning customer's phone
Photo: Kohl’s

Can Kohl’s boost marketing effectiveness with machine learning?

It’s no secret that 2022 was a down year for Kohl’s due to various factors. The company is betting that a customer-centric approach and a rebranded loyalty program will help it return to the path of profitable growth.

Christie Raymond, Kohl’s chief marketing officer, during a session “Merging Data with Creativity in Order to Effectively Market to Customers in Today’s Changed Retail Landscape” last week at eTail West Palm Springs 2023, discussed how the retailer is utilizing data and insights to inform all its marketing strategies, campaigns and loyalty programs.

The company wants to bring in younger, more diverse customers while retaining older core shoppers to boost sales and profits. “You’re trying to build loyalty, but at the end of the day, you need to drive business,” Ms. Raymond said.

Kohl’s is a heavy user of machine learning, having spent 2022 building up its analytics team. The retailer learned core customers weren’t leveraging all of its loyalty programs (Yes2You, Kohl’s Card, Kohl’s Cash). Newer customers found the programs confusing. Kohl’s consolidated the programs into a single program rebranded as Kohl’s Rewards, which quickly showed an increase in enrollment and redemption rates. Kohl’s Rewards has more than 30 million members.

With the new simplified program, Kohl’s can capture first-party data in-store and through their digital commerce platform, helping them better understand and connect with more valuable higher-spending omnichannel shoppers. “The biggest focus is getting store shoppers into our loyalty program,” said Ms. Raymond, “it’s a huge priority for store associates.”

Ms. Raymond charged her team with developing compelling creative concepts and performance marketing campaigns based on data to tell Kohl’s story to its key customer targets. Creative teams have the flexibility to bring the brand voice into marketing visuals and channels. Machine learning optimizes media mix, targeting, promotions, media platforms and other activities. Real-time data and social media insights are fed into marketing to course correct.

BrainTrust

"Data analysis is important, but how you use the analytics to build marketing programs is just as important. Time needs to be spent understanding the analytics."

Camille P. Schuster, PhD.

President, Global Collaborations, Inc.


Discussion Questions

DISCUSSION QUESTIONS: Is there a disconnect between data analysis and marketing in retail? Will Kohl’s use of data analytics in its marketing attract a younger customer base?

Poll

22 Comments
Oldest
Newest Most Voted
Inline Feedbacks
View all comments
John Lietsch
Active Member
1 year ago

“‘You’re trying to build loyalty, but at the end of the day, you need to drive business,’ Ms. Raymond said.” That’s the key. Business hasn’t changed EVER. It’s still about making money and making money requires happy, loyal customers. Data analytics can help but, as demonstrated by the consolidation of its loyalty programs, Kohl’s problems can’t be solved by analytics alone. However analytics can do what it has always done and provide Kohl’s with better information to hopefully make and execute better business decisions.

Dion Kenney
1 year ago

The comment “the biggest focus is getting store shoppers into our loyalty program” is more indicative of Kohl’s problem than they may have intended it to be. I like Kohl’s. My household needs most of the kinds of products they carry. And they are conveniently located. But I rarely think of them when it’s time to buy. Why? I have a Kohl’s card, have purchased from them online, and am subscribed to their email list, yet I still don’t get any inspiring emails that speak to me. I hope the new team and newly defined mission can mine the treasure trove of information they have on me (age, location, past purchases, demographics, etc.) and create custom-tailored, effective marketing.

David Naumann
Active Member
1 year ago

There is often no shortage of customer data in retail, but the key is to turn the data into actionable insights. Retailers have been analyzing customer data for years to better segment and communicate with customers. Leveraging machine learning/AI to make better sense of data may help Kohl’s make smarter marketing decisions. And combining its three loyalty programs into one Kohl’s Rewards program is a smart move. Loyalty and rewards programs are a huge driver for Kohl’s customer base and making it simple and easy is imperative.

Jenn McMillen
Active Member
1 year ago

Using data to create a more personalized, relevant experience is something that applies to shoppers of all ages. If machine learning enables that, then Kohl’s should stay the course and probably invest more.

Lee Peterson
Member
1 year ago

I just read a great piece on this that basically says, machines can tell us what is, but cannot accurately tell us what needs to be. I suggest that Kohl’s check it out. No machine is going to be better at telling them how to solve their problems than a talented group of leaders, which we’re not really sure they have at this stage of their downward slide. I’d skip the machines and let the customer and some more innovative thinking lead the way. And history tells us that having financial leaders at retail will only exacerbate or delay their issues. Just ask Gap.

Gene Detroyer
Noble Member
1 year ago

In recent discussions, the BrainTrust has signaled a huge disconnect between data availability, analysis and marketing execution. Apparently, Kohl’s recognizes that. I suspect most other retailers are also wringing their hands on how best to use data.

The problem is, even if Kohl’s finds their use of data to be world-class, they are still “Kohl’s.” What the data may tell them is to close more doors.

DeAnn Campbell
Active Member
1 year ago

Every company is different, but traditionally there has been autonomy in the marketing division that has excluded decision makers from other departments. But I’m happy to see this mindset is beginning to change as more retailers realize the increased speed and flexibility that can result from dropping siloed corporate structures.

Ian Percy
Member
1 year ago

“Konfusing Kohl’s” is how I’d describe it too! So many coupons, Kohl’s Cash, etc. drives me crazy especially when one needs to print the coupon found at the bottom of a seven page mass email. Add the facts that apparently no one works on the floor helping customers, and that most coupons don’t apply to the majority of brands they carry but they don’t tell you which qualify and which don’t. So yes there is a disconnect! They try to stock for the younger population but here in Arizona you won’t find one in Kohl’s. For me the final blow is that their buyer must be about 35 with no clue about what fashion works for the huge senior population here who aren’t looking for slim-fit jeans with holes in them.

Gary Sankary
Noble Member
1 year ago

The promise of machine learning is that it will help businesses ask questions they may not have even thought about. I’m hopeful that Kohl’s (and others) will be able to leverage this technology to find discrete insights in their data that can help them fine-tune strategies that are more relevant to their existing and prospective customer base. And to find the messages that will resonate with new target audiences that they so desperately need to drive growth.

Camille P. Schuster, PhD.
Member
1 year ago

Data analysis is important, but how you use the analytics to build marketing programs is just as important. Time needs to be spent understanding the analytics. Simplifying the rewards programs is definitely a good move. Now it is important to make sure the computer interface on every device is easy to use when viewing products, and that ordering products, using the rewards, paying for products, and the billing process all work smoothly. No consumer, especially younger consumers, will continue with a retailer if any one of those processes fail to work smoothly.

Ryan Mathews
Trusted Member
1 year ago

Machine learning without a contextual framework is just slightly better than useless. So yes there is a huge, and growing, chasm between analytics and marketing. Retailers need to engage marketers before the machine learning code is written, not after.

Neil Saunders
Famed Member
1 year ago

If Kohl’s wants to bring in new and younger customers it needs to look deeply at its offer and its stores. The best marketing and loyalty scheme in the world isn’t going to appeal to the younger crowd if those essentials are not right. I am sure that machine learning has a role to play, but it’s a secondary consideration after getting the primary retail functions in order.

Dick Seesel
Trusted Member
1 year ago

I feel like Kohl’s has recognized — and attempted to simplify — the confusion over its overlapping loyalty programs a while ago. (In fact, there is probably a BrainTrust discussion about it going back several years.) If advances in data analytics enable Kohl’s to address the problem once and for all, it will be a positive.

That being said — and speaking as a former employee and current customer — the key to Kohl’s turnaround is to focus on simplification in its assortment planning and the resulting store experience, not just its loyalty programs. (I used to say that Kohl’s stock symbol, KSS, stood for “Keep It Simple, Stupid” and it was a philosophy that worked.) Machine learning and other tools can help, but only if merchants and store executives embrace the message.

Cathy Hotka
Trusted Member
1 year ago

Many retailers have vast troves of data that they cannot leverage adequately. Given the cost of these programs, it’s critical that retailers learn how to assess their effectiveness.

Ian Percy
Member
Reply to  Cathy Hotka
1 year ago

Absolutely right Cathy. What is needed is not more data, it’s more discernment.

Brandon Rael
Active Member
1 year ago

There is an endless stream of data availability in the retail and consumer sectors. The challenge we have seen is determining how best to collect, curate, and operationalize your strategies by leveraging relevant and real-time insights. Kohl’s is making the correct investments in data and analytics capabilities powered by machine learning. However the challenge they face is in the marketing, personalization, and ultimately the merchandising and store operation execution.

Analytics and insights are absolutely critical in addressing personalized experienced and empowering loyalty programs to provide value to consumers. Kohl’s has to leverage the correct value drivers to ensure that their marketing and personalized offers resonate with its core customers and attract new ones. In addition, the retail fundamentals are always critical around merchandising execution, store operations, and customer experience.

Doug Garnett
Active Member
1 year ago

It took machine learning to see their rewards programs confused customer?There is nothing in this discussion which makes me optimistic for Kohl’s. The mere idea that they think machine learning is a competitive advantage suggests it will be a long time before they recover their economic strength. Beside, we’ve heard this refrain before — for the last decade it’s been repeated by other companies, then the idea has quickly disappeared as they only discovered a tiny bit of opportunity and no competitive advantage.

Joel Rubinson
Member
1 year ago

Leveraging data assets is a huge part of modern marketing. My work has shown that the right behavioral segment can deliver up to 19 TIMES the return on advertising, repeatably for each and every campaign. However my work was theory and math driven, not based on machine learning. In fact, I might say that “machine learning” is an oxymoron like “jumbo shrimp.” You actually might learn close to nothing from machine learning because it is parochial to the particular data set. No generalizability and no principles revealed, just data patterns.

Ananda Chakravarty
Active Member
Reply to  Joel Rubinson
1 year ago

The codification of machine learning is that the machine is learning and self-correcting as opposed to the humans or handlers, so I’m not sure it’s such an oxymoron in that context. Also machine learning has wide implications that include generalizations and principles — deep learning tools such convolutional neural networks and language learning models are all considered machine learning. These don’t just rely on data patterns alone and in many cases can be generalized to broader data sets. Still, your point about data assets is spot on and critical to marketing as you mention which doesn’t always need ML. Good thoughts.

Ananda Chakravarty
Active Member
1 year ago

Data is just a tool and like all tools needs to be maintained, used in the proper way, and used by those who are skilled in its usage. What Kohl’s has done so far has been collecting their tool (loyalty program data) and just found the skilled engineers, architects, and scientists to use it. Applying the data to marketing is their current learning step and that is usually the challenging part. The machine learning component also is a tool that Kohl’s must master towards its goals, but it is a much smaller part of their equation. The first step is figuring out how to apply their data to marketing initiatives and campaigns.

Mark Price
Member
1 year ago

There is no disconnect between data analysis and marketing in retail when daily analysis is structured to provide insight, target selection, and advance measurement that informs marketing strategy and evaluates marketing execution. The move to measured marketing does not threaten marketing at all: rather it provides insight and accountability that focuses resources, and identifies strategies and tactics that improve acquisition and customer retention.

Kohl’s can use machine learning to improve customer acquisition and build their base among younger customers. The critical factor is that Kohl’s must have the product assortment that will meet the needs of those customers.