March 27, 2013
When Will Retailers Patch the Holes in My Data?
There’s no doubt a massive amount of my personal information is floating around out there in the algorithmosphere. Some of which, I’m sure, I have no idea about. My concern, unlike some others, is not an Orwellian loss of privacy but whether or not the companies I do business with will ever be able to use this data in a way that will be of some value to me.
Too often — which in this context means just about 100 percent of the time — I’m provided recommendations or offers based on incomplete or incorrect knowledge. Some recent examples:
- A direct mailing from a local mass merchandiser with special offers on baby items. Yes, we do purchase baby wipes, but check your records and you’ll see it’s been years since we bought diapers. We never purchased infant formula (the resident RN is also a board certified lactation consultant). In other words, our use of wipes has nothing to do with a baby in the house.
- A music download service continues to email recommended selections in the Electronica genre despite my account (not the same thing as me) having placed only one such order in nearly 10 years. Evidence the site has to the contrary are large annual purchases of music in the Americana, blues, rock and soul genres.
- I check out at a local supermarket buying my favorite type of Greek yogurt and am handed a coupon for a competitive item. I don’t want to switch. I’ve already tried the other stuff and I have nothing good to say about its taste. Give me a coupon for what I already buy.
The biggest issue I see with retailers’ use of data, aside from not mining it insightfully, is that they don’t have the complete picture. To know what I want and how I shop requires having access to information beyond a store’s scan data or orders placed on a single website. There are certain food items, for example, that I only buy from a given store. Why? Because while other merchants may stock a particular company’s products, they don’t stock the SKU I want.
At the NRF Big Show in January, I spoke with a number of Big Data experts who all claimed that a solution was coming soon. Retailers would soon know what I was buying in other places. This, they all claimed, would be done without endangering my information’s safety.
Nielsen Catalina Solutions, according to an Advertising Age report, is adding data from financial sources such as credit cards and banks to information it is already grabbing from scan data to provide a more complete picture of shopper behavior. I’ve also heard that others are doing something similar. Let’s hope they get it right, for my shopping sake.
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Discussion Questions
Do you think retailers are close to patching the holes in consumer data that will enable them to market in a more personalized fashion? Where do you see the biggest challenges facing merchants in this respect?
Poll
It’s clear (without taking one side or another) that the Democrats managed “big data” more effectively than the Republicans in the last election. A lesson learned for all retailers and marketers: Put the time, effort and expense into your data warehouse and it will pay dividends. Among retailers, Amazon has long been at the top of the list for effective data management and addressing specific consumer interests. Macy’s probably leads the pack of more traditional omnichannel retailers, especially through its “My Macy’s” initiative and the micro-targeting of its print offers.
Bottom line: The capability is there because the top-tier retailers are already doing great things with “Big Data.” Those who aren’t prepared to make the same commitment will have to deal with the consequences.
Couldn’t agree more. My son struggles with Moosejaw believing he’s a girl after he let his sister put her purchases on his “points” program. The “system” only knows what goes in, and most aren’t set up to get a practical override from humans who are trying to help other humans.
I would love retailers to complete the picture, but there has to be a way to allow or select a level of desired personalization to enhance value. Without being able to filter what’s being pushed my way, it’s all still pretty annoying.
We need a pull model. Consumers want a control button on big data.
Whether we talk about customer data as George is doing here, the leadership of complex corporations, the education experience of our youth, how our government runs or particle physics…the secret sauce is always in those ‘holes’ or spaces. It’s not the ‘thing’, it’s the spaces between the ‘things’ that hold all the possibilities that are possible.
This thought is brought to you by the Letter ‘A’ – which stands for ALIGNMENT. The lack of alignment is what destroys the customer experience and robs companies of both their profit and ability to innovate and respond. When we align all our energies toward our highest possibilities an entire new world opens up.
Please…for George’s sake!
PS: You do NOT want a “patch.”
With all of the available data, we are still a number of years away from efficiently developing individual profiles of consumers and then delivering a personalized communication experience. There are large quantities of data to be harnessed, and most retailers do not have the budgets to harvest and process the data.
Retailers need to see that harvesting and processing data will produce a profitable return on investment. Then they will begin to tackle big data, one step at a time.
Consumer data is a dandy and necessary sales tool when clear, accurate, and not misused. Other the hand, personalized data is saturating the heavy clouds of information gathering. But who really benefits by knowing when your spouse gargles or takes a shower?
There are over 300 million consumers in the U.S. When we finally are able to get personalized information on everyone, a targeted panacea, will the mystical fun in retailing (vs. the science of personal data invasion) become fashionable again?
I’m going to take the opposite position, George, and say, “Gee—how much more do you want Big Brother looking over your shoulder?” I don’t want to be marketed to on a personalized fashion very much, and I’m hoping they never get close to patching the holes. Maybe the question is whether they can do it faster than baby boomers can rebel against the invasion of privacy.
Yes and no. The problem isn’t the data needing to be patched, it’s managing it to extract valuable shopper insights. With Big Data tracking almost everything people purchase, it’s conceivable that the answers are already there, retailers just haven’t found a way to extract them so that they are marketing to consumers in a meaningful way.
The biggest challenge is being able to acquire, process, and distribute this information in a cost-effective, quick, and efficient manner so that shoppers get the most from their retail experience. The answers are definitely there, it’s just a matter of investing in the right tools and technology to make data effective for retailers.
Hey George, not all of the examples you cite are errors in shopper analytics. If you get coupons for a competitive product rather than for the item you buy, that’s because the competitor wants you to try theirs. They KNOW you’re buying the other stuff. Why should the maker of the stuff you already buy give you an “unwarranted” discount? You’d buy that stuff regardless, right? That’s why I hate the majority of “loyalty” programs in grocers. They give mass discounts to items you’d buy anyway.
To respond to the point of the article, I believe big data is getting managed better by the minute by merchants and CPGs. There are some really great tools that are delivering tangible profitability through effective analysis.
Big Data will go beyond “patching holes,” as sensor fusions enabled by the Internet of Everything drive to new levels of fidelity. This will create a shift from reactive (looking in the rear view mirror approach—your example of coupon after POS) to more real-time and predictive (the right incentive for you specifically, while you are in the yogurt aisle).
Retailers are moving in this direction but it requires investment, new skills, and for many, a cultural shift to being good at fast cycle innovation. The next 24 months will see many retailers moving from “toe dipping” to making this transformation.
One of my favorite examples that gives a sense of the potential is the researchers who use algorithms from smartphone tracking to predict where you will be in 24 hours with an average error of only 20 meters.
While there are certainly databasing issues out there that are slowing the progress of truly effective relevant communications, I find the biggest gap within most retailers is having a cogent strategy that leverages the data they already have access to.
Retailers that are loaded up on customer data many times use it for promotional purposes for perceived quick returns on communications and offers that are not well thought out in terms of customer benefit. However, those retailers that take a longer view, understand that “campaigns” that yield a learning dialogue with their customers may not show an immediate financial return, but over time, build the type of communications that are truly meaningful and relevant to the consumer that foster profitable and returning customers.
The notion that database marketing programs are still sending “competitive brand offers” to shoppers who are loyal to another brand, or pet or baby category offers to others that have neither in their household, indicate to me that that there are flaws in the communication strategy, not in the database or the communication tools that connect to it.
The big opportunity here is giving customers a choice, instead of trying to divine what they might want.
Retailers could ask customers what kinds of things they’re most interested in—black pants, new ethnic food, accessories for their smart phone—then deliver offers on those. Until the customer can indicate what he or she wants, the retailer will be guessing, despite pricey investments in Big Data.
My frustration with this topic is, instead of trying to GUESS what you want, why can’t retailers just ask you? Why can’t I, as a shopper, log into Target’s site with my Red Card and say “Hey. Don’t give me offers for Pepsi because I hate the stuff and won’t drink it, let alone buy it. And by the way, don’t bother sending me daily text deals that contain baby stuff. I’m out of that market and it’s annoying that you can’t tell that already.”
Part of the problem is the money involved. Is Target deciding what coupons to hand me at checkout? No. Catalina is (I’m assuming). And they’re not in it for me, they’re in it for whatever brands are paying them to push offers at me. And Target may very well know that I don’t want baby offers from the daily deals, but they don’t have a way yet to segment those offers—or maybe they just aren’t getting enough uptake to make it worth their while.
I totally agree that if consumers can see the value—as in, save me time or save me money—then they are more than happy to share data about themselves to make that happen. What’s annoying is that retailers seem diametrically opposed to the concept of ASKING them. It doesn’t even have to be as complex as preferences on a loyalty card site. A simple “Do you want more offers like this one?” would do wonders.
As a statistician, it is pretty clear that perfect data does not exist. Even if it did, to avoid privacy issues brands would have to be very cautious and careful about how they used it. This essentially produces similar results for the consumer. When brands have pushed the boundaries, consumers push back—reference the Target pregnancy analytics debate or RapLeaf Online data tracking. Any company plugging the data holes will be very careful when collecting and allowing personal shopping data to be used to avoid the public eye.
George, this is terrible and I am sure that Al McClain is using your name to have more crap sent to your home!
The data game is rolling along well and more and more granular level data about the shopper and their habits, joys, and dislikes is being pulled together and properly managed. The problem is the old applications or in many cases customer “best of breed” apps created in the old days to leverage the data. These apps lack the proper forecasting and alignment science that tightly maps or links the right data to the right shopper at the right time and makes them SMILE!
The challenge is to get the retailers to make the shift from old apps to the new apps (like Amazon did and other retailers have done) and make the best use of the shopper data—along with keeping the info secure and blocking people like Al from abusing George.
Tom…worried about The George Data Factor….
We all experience mistimed or irrelevant offers from the brands we shop, and I identify with the author’s statement of his case. Two thoughts:
Some of the most successful data firms have built their reputation through trial and error. People tend to focus on the end goal and not embrace the process needed to arrive at the goal. I am okay with brands slightly missing the mark, but am less satisfied that there is no feedback mechanism through which I can express the missed opportunity.
The issue is that data will never tell the whole story. Marketers need to combine the non-transactional interactions online with transaction records to arrive at a better understanding of customers. Social mentions and sentiment analysis are a good start, but direct survey in context of a trusted relationship (date I say a customer club or loyalty program) can lead to the most accurate expression of preferences by customers.
Retailers embracing this part of the measurement discipline will become more relevant to their customers.
I am going to agree with Dr. Needel and state I really don’t want all the information that is “out there” about me and my family to be interconnected. Perhaps it’s a generational issue.
I was taught not to over share information versus the kids today that post on Facebook, YouTube and every other place everything they do or tweet every five minutes what is happening in their lives.
There is no shortage of data for most retailers, but unfortunately many are still a good distance from using customer data in a more personalized and relevant manner. There are two big challenges facing merchants in terms of better using customer data:
- Systems and technologies. Retailers typically have dated and siloed systems that make it a significant challenge to have a single (or often even a decent) view of customers. They seem to prioritize investments elsewhere though that is rapidly changing. We are seeing, talking and working with more retailers than ever and working to solve this problem, usually “ASAP”!
- Marketing and business strategies. Too many retailers still believe in replacing traditional mass marketing (TV, ROP, etc.) with mass email marketing, rather than relationship marketing that is more customer-centric and data driven. Like the challenges on the systems-side, and often in tandem with addressing those challenges, more retailers are testing and finding that they can actually target fewer customers in a more targeted manner and yield the same (or better) results.
My question is: Should they?
Understanding that just because I Googled about gardening one weekend does not mean that I am a gardener. I was simply attending a workshop and the project my team took on was abut gardening. This kind of thing happens all the time as also expressed by the author. Retail does not need, nor can they really, patch that hole.
What I’m saying is that retail does not need to guess my every move and try to market to me. We don’t like it and it often backfires, again referring to the examples noted by the author.
What retail can do is look at the habits of customers over a longer term. If they are your best customers, you will surely have long term shopping habits.Then you can do some personalizing. You can also look across demographics of those same customers and determine personas that can be used to provide great customer experiences. Get it?
Just because we have all this data doesn’t mean that we need to harness all of it. Just figure out the pieces that make the most sense for each business and go from there. Voila!
Sythesizing the comments here, I have 2 observations:
- People send you stuff you don’t want—but logically could want—in hopes of changing your mind…that’s what promotion is all about;
- As various people named Steve pointed out, if someone so misses the boat that they send you something you don’t even have a possibility of wanting, then it likely means they really don’t know all about you…yet, at least. Be glad.
It has been possible for decades to patch the holes in retailer’s understanding of customers and execute on those insights in merchandising and brand decisions. With computing hardware and software advances, it has never been a more exciting time to be a retailer—large or small, old or new.
Advanced analytics that were used by some for many years are more accessible to all with visual analytics and forward-looking advanced analytics. The biggest challenge for retailers is often getting started. It is not easy work to shore up your foundation and all the IT jargon can be intimidating.
Retailers can build a retail analytics foundation that drives current and future strategies, finds innovative ideas, and allows execution on changing strategies and tactics. Taking one step at a time on a larger plan, retailers gain short-term and sustainable long-term benefits and competitive advantage and build a foundation that is strong for years to come.
I think Nikki Baird sums it up quite nicely. Amazon does a great job of asking you to not only rate their suggested items, but also asks you about certain purchases. For example, was it a gift item, and so you’re unlikely to purchase similar items in the future?
A combination of asking the consumer what they’re interested in and then following up on those suggestions with targeted promotions is a much better way of getting the consumer to open up and share that information with you. And it does not require a massive investment—as with any initiative, retailers could test by starting small with a specific set of items or products, learn what works, and scale accordingly.
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It’s clear (without taking one side or another) that the Democrats managed “big data” more effectively than the Republicans in the last election. A lesson learned for all retailers and marketers: Put the time, effort and expense into your data warehouse and it will pay dividends. Among retailers, Amazon has long been at the top of the list for effective data management and addressing specific consumer interests. Macy’s probably leads the pack of more traditional omnichannel retailers, especially through its “My Macy’s” initiative and the micro-targeting of its print offers.
Bottom line: The capability is there because the top-tier retailers are already doing great things with “Big Data.” Those who aren’t prepared to make the same commitment will have to deal with the consequences.
Couldn’t agree more. My son struggles with Moosejaw believing he’s a girl after he let his sister put her purchases on his “points” program. The “system” only knows what goes in, and most aren’t set up to get a practical override from humans who are trying to help other humans.
I would love retailers to complete the picture, but there has to be a way to allow or select a level of desired personalization to enhance value. Without being able to filter what’s being pushed my way, it’s all still pretty annoying.
We need a pull model. Consumers want a control button on big data.
Whether we talk about customer data as George is doing here, the leadership of complex corporations, the education experience of our youth, how our government runs or particle physics…the secret sauce is always in those ‘holes’ or spaces. It’s not the ‘thing’, it’s the spaces between the ‘things’ that hold all the possibilities that are possible.
This thought is brought to you by the Letter ‘A’ – which stands for ALIGNMENT. The lack of alignment is what destroys the customer experience and robs companies of both their profit and ability to innovate and respond. When we align all our energies toward our highest possibilities an entire new world opens up.
Please…for George’s sake!
PS: You do NOT want a “patch.”
With all of the available data, we are still a number of years away from efficiently developing individual profiles of consumers and then delivering a personalized communication experience. There are large quantities of data to be harnessed, and most retailers do not have the budgets to harvest and process the data.
Retailers need to see that harvesting and processing data will produce a profitable return on investment. Then they will begin to tackle big data, one step at a time.
Consumer data is a dandy and necessary sales tool when clear, accurate, and not misused. Other the hand, personalized data is saturating the heavy clouds of information gathering. But who really benefits by knowing when your spouse gargles or takes a shower?
There are over 300 million consumers in the U.S. When we finally are able to get personalized information on everyone, a targeted panacea, will the mystical fun in retailing (vs. the science of personal data invasion) become fashionable again?
I’m going to take the opposite position, George, and say, “Gee—how much more do you want Big Brother looking over your shoulder?” I don’t want to be marketed to on a personalized fashion very much, and I’m hoping they never get close to patching the holes. Maybe the question is whether they can do it faster than baby boomers can rebel against the invasion of privacy.
Yes and no. The problem isn’t the data needing to be patched, it’s managing it to extract valuable shopper insights. With Big Data tracking almost everything people purchase, it’s conceivable that the answers are already there, retailers just haven’t found a way to extract them so that they are marketing to consumers in a meaningful way.
The biggest challenge is being able to acquire, process, and distribute this information in a cost-effective, quick, and efficient manner so that shoppers get the most from their retail experience. The answers are definitely there, it’s just a matter of investing in the right tools and technology to make data effective for retailers.
Hey George, not all of the examples you cite are errors in shopper analytics. If you get coupons for a competitive product rather than for the item you buy, that’s because the competitor wants you to try theirs. They KNOW you’re buying the other stuff. Why should the maker of the stuff you already buy give you an “unwarranted” discount? You’d buy that stuff regardless, right? That’s why I hate the majority of “loyalty” programs in grocers. They give mass discounts to items you’d buy anyway.
To respond to the point of the article, I believe big data is getting managed better by the minute by merchants and CPGs. There are some really great tools that are delivering tangible profitability through effective analysis.
Big Data will go beyond “patching holes,” as sensor fusions enabled by the Internet of Everything drive to new levels of fidelity. This will create a shift from reactive (looking in the rear view mirror approach—your example of coupon after POS) to more real-time and predictive (the right incentive for you specifically, while you are in the yogurt aisle).
Retailers are moving in this direction but it requires investment, new skills, and for many, a cultural shift to being good at fast cycle innovation. The next 24 months will see many retailers moving from “toe dipping” to making this transformation.
One of my favorite examples that gives a sense of the potential is the researchers who use algorithms from smartphone tracking to predict where you will be in 24 hours with an average error of only 20 meters.
While there are certainly databasing issues out there that are slowing the progress of truly effective relevant communications, I find the biggest gap within most retailers is having a cogent strategy that leverages the data they already have access to.
Retailers that are loaded up on customer data many times use it for promotional purposes for perceived quick returns on communications and offers that are not well thought out in terms of customer benefit. However, those retailers that take a longer view, understand that “campaigns” that yield a learning dialogue with their customers may not show an immediate financial return, but over time, build the type of communications that are truly meaningful and relevant to the consumer that foster profitable and returning customers.
The notion that database marketing programs are still sending “competitive brand offers” to shoppers who are loyal to another brand, or pet or baby category offers to others that have neither in their household, indicate to me that that there are flaws in the communication strategy, not in the database or the communication tools that connect to it.
The big opportunity here is giving customers a choice, instead of trying to divine what they might want.
Retailers could ask customers what kinds of things they’re most interested in—black pants, new ethnic food, accessories for their smart phone—then deliver offers on those. Until the customer can indicate what he or she wants, the retailer will be guessing, despite pricey investments in Big Data.
My frustration with this topic is, instead of trying to GUESS what you want, why can’t retailers just ask you? Why can’t I, as a shopper, log into Target’s site with my Red Card and say “Hey. Don’t give me offers for Pepsi because I hate the stuff and won’t drink it, let alone buy it. And by the way, don’t bother sending me daily text deals that contain baby stuff. I’m out of that market and it’s annoying that you can’t tell that already.”
Part of the problem is the money involved. Is Target deciding what coupons to hand me at checkout? No. Catalina is (I’m assuming). And they’re not in it for me, they’re in it for whatever brands are paying them to push offers at me. And Target may very well know that I don’t want baby offers from the daily deals, but they don’t have a way yet to segment those offers—or maybe they just aren’t getting enough uptake to make it worth their while.
I totally agree that if consumers can see the value—as in, save me time or save me money—then they are more than happy to share data about themselves to make that happen. What’s annoying is that retailers seem diametrically opposed to the concept of ASKING them. It doesn’t even have to be as complex as preferences on a loyalty card site. A simple “Do you want more offers like this one?” would do wonders.
As a statistician, it is pretty clear that perfect data does not exist. Even if it did, to avoid privacy issues brands would have to be very cautious and careful about how they used it. This essentially produces similar results for the consumer. When brands have pushed the boundaries, consumers push back—reference the Target pregnancy analytics debate or RapLeaf Online data tracking. Any company plugging the data holes will be very careful when collecting and allowing personal shopping data to be used to avoid the public eye.
George, this is terrible and I am sure that Al McClain is using your name to have more crap sent to your home!
The data game is rolling along well and more and more granular level data about the shopper and their habits, joys, and dislikes is being pulled together and properly managed. The problem is the old applications or in many cases customer “best of breed” apps created in the old days to leverage the data. These apps lack the proper forecasting and alignment science that tightly maps or links the right data to the right shopper at the right time and makes them SMILE!
The challenge is to get the retailers to make the shift from old apps to the new apps (like Amazon did and other retailers have done) and make the best use of the shopper data—along with keeping the info secure and blocking people like Al from abusing George.
Tom…worried about The George Data Factor….
We all experience mistimed or irrelevant offers from the brands we shop, and I identify with the author’s statement of his case. Two thoughts:
Some of the most successful data firms have built their reputation through trial and error. People tend to focus on the end goal and not embrace the process needed to arrive at the goal. I am okay with brands slightly missing the mark, but am less satisfied that there is no feedback mechanism through which I can express the missed opportunity.
The issue is that data will never tell the whole story. Marketers need to combine the non-transactional interactions online with transaction records to arrive at a better understanding of customers. Social mentions and sentiment analysis are a good start, but direct survey in context of a trusted relationship (date I say a customer club or loyalty program) can lead to the most accurate expression of preferences by customers.
Retailers embracing this part of the measurement discipline will become more relevant to their customers.
I am going to agree with Dr. Needel and state I really don’t want all the information that is “out there” about me and my family to be interconnected. Perhaps it’s a generational issue.
I was taught not to over share information versus the kids today that post on Facebook, YouTube and every other place everything they do or tweet every five minutes what is happening in their lives.
There is no shortage of data for most retailers, but unfortunately many are still a good distance from using customer data in a more personalized and relevant manner. There are two big challenges facing merchants in terms of better using customer data:
My question is: Should they?
Understanding that just because I Googled about gardening one weekend does not mean that I am a gardener. I was simply attending a workshop and the project my team took on was abut gardening. This kind of thing happens all the time as also expressed by the author. Retail does not need, nor can they really, patch that hole.
What I’m saying is that retail does not need to guess my every move and try to market to me. We don’t like it and it often backfires, again referring to the examples noted by the author.
What retail can do is look at the habits of customers over a longer term. If they are your best customers, you will surely have long term shopping habits.Then you can do some personalizing. You can also look across demographics of those same customers and determine personas that can be used to provide great customer experiences. Get it?
Just because we have all this data doesn’t mean that we need to harness all of it. Just figure out the pieces that make the most sense for each business and go from there. Voila!
Sythesizing the comments here, I have 2 observations:
It has been possible for decades to patch the holes in retailer’s understanding of customers and execute on those insights in merchandising and brand decisions. With computing hardware and software advances, it has never been a more exciting time to be a retailer—large or small, old or new.
Advanced analytics that were used by some for many years are more accessible to all with visual analytics and forward-looking advanced analytics. The biggest challenge for retailers is often getting started. It is not easy work to shore up your foundation and all the IT jargon can be intimidating.
Retailers can build a retail analytics foundation that drives current and future strategies, finds innovative ideas, and allows execution on changing strategies and tactics. Taking one step at a time on a larger plan, retailers gain short-term and sustainable long-term benefits and competitive advantage and build a foundation that is strong for years to come.
I think Nikki Baird sums it up quite nicely. Amazon does a great job of asking you to not only rate their suggested items, but also asks you about certain purchases. For example, was it a gift item, and so you’re unlikely to purchase similar items in the future?
A combination of asking the consumer what they’re interested in and then following up on those suggestions with targeted promotions is a much better way of getting the consumer to open up and share that information with you. And it does not require a massive investment—as with any initiative, retailers could test by starting small with a specific set of items or products, learn what works, and scale accordingly.