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5 Value Drivers to Consider for Big Data in Retail

 


Data is the new oil? No: Data is the new soil. (David McCandless, TEDGlobal)

The quest to cultivate useful insights from data is nothing new. From Frederick Winslow Taylor’s time-and-motion studies on worker productivity over a century ago up to today, the ability to gain true insight has been an on-going pursuit for many. The goal, according to business leaders and technologists, will be a smarter world, with more efficient companies, better-served customers and superior decisions guided by data and analytics. Yet it is abundantly clear that data, by itself, holds little value unless you put the right human power behind it that knows which questions to ask and how to glean insights from the data. As we like to say here at First Insight, “Data is Ubiquitous – Insights are Rare. ”One of the biggest areas in retail where Big Data can make a significant impact on the business is new products. Why should retailers consider using analytics to successfully select and price new products? I’ll give you two reasons:

  • Greater than 50% of new products fail. (MIT Sloan)
  • 11% of new items can bear a higher opening price point.
If these aren’t compelling enough numbers to consider analytics on new products and in the product development cycle, I’ll give you one more:
  • Excess inventory, deep markdowns and missed upside cost retailers $250 billion a year.
The right predictive analytics tool can drive value in 5 key areas when it comes to new products:
  • Product Selection – Pick the winners and avoid the “dogs”
  • Pricing – Many products can bear a higher price than originally planned
  • Product Modification – Modify designs before they are finalized
  • Deeper Buys – Buy more of the winners and less of the loser
  • Cost Savings – Current product testing methods are time-consuming, costly and yield little to no actionable insight
Please take two minutes to watch our brand new video highlighting First Insight’s vision on how to address the challenges of successful new product launches.


Don’t Be a “Retail Laggard” – Separating Signal from Noise Drives Results

 

 

 

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When you buy a car, there are two factors that come into play before you turn the key and drive away: facts and feelings. 

The facts are easy: MPG, horsepower, technology, number of seats, safety features. But when it comes to your feelings about the car, a completely different part of the brain kicks in. Is this car “me”? Does it feel “right”? Do I love the color? Are the seats heated? Do I feel safe?

In retail, experience and intuition will always play a role, but today’s environment requires a combination of experience and data to maintain a competitive edge.

In a report released in January 2014 entitled “Retail Analytics Moves To The Frontline,” Retail Systems Research (RSR) presented a current view of the state of analytics and where retailers see value in using data across various areas of the organization. Retail was, and for some still is, an emotion-driven business. However, as the RSR report states, it is now more evident than ever that the retail industry is moving towards a stronger mix of data AND intuition-based decision-making.

We are accustomed to seeing data analytics used by marketing departments and the supply chain organization. What stood out to me in the RSR report was the fact that 80% of product development and merchandising departments are now data-oriented when it comes to decision-making. On the flip side, more than 40% of “laggards” (retailers with less than 3% comp store/channel sales growth) are merchandising and marketing solely on experience and intuition.  

For retail “winners” (retailers with greater than 3% comp store/channel sales growth), the area listed as the top opportunity for greater use of analytics to drive business results was “More intelligent allocation and optimization of products based on customer insights.” 

At First Insight we are seeing an acceleration in the number of retailers using our solution for just this purpose. Just last week, Trefis (a leading stock analysis and forecasting firm) wrote an article discussing the impact they expect First Insight’s predictive analytics to have on Abercrombie & Fitch’s business:

By leveraging First Insight’s data, Abercrombie will be able to invest in more relevant products, which can help it attract customers and operate with fewer markdowns.

Hidden within the oceans of retail data are “signals” which contain insight that can help retailers figure out what customers want that require quick action. But not all “signals” that contain insights are obvious. There are benefits in “weak” signals, but it takes discipline and the right analytics to find these signals and make them actionable.

Weak Signals Produce Winning Ideas
An example of the successful identification and use of “weak” signals by Nordstrom was outlined in a February 2014 article by McKinsey and Company titled, “The Strength of ‘Weak Signals.’” 

Nordstrom took an early interest in engaging consumers through social media and found that it was an excellent approach to identifying which products were resonating with customers in an open, social environment.

The article stated, “Spotting an opportunity to share this online engagement with in-store shoppers, the company recently started displaying popular items in two of its Seattle-area stores. When early results were encouraging, Nordstrom began rolling out the test more broadly to capitalize on the site’s appeal to customers as the “world’s largest ‘wish list.’ ”

Spotting these signals can yield actionable results, and applying predictive analytics can give retailers a much more focused picture that exposes the true customer behavior they are looking for.

Plan, Execute and Manage - Looking Forward, Not Back
Winning retailers know that data and analytics support the decision-making process rather than replace it.  According to the RSR report, 66% of respondents said a mix of data and experience were used to make decisions in the product development group, and 69% of respondents said the same in the merchandising organization.

The most powerful signals in retail come from consumers. Identifying weak signals consumers generate through consumer engagement takes discipline. Today, technology makes it easier to convert these signals into clear decisions which drive margin gains. The power of predictive analytics lies in finding these signals and listening to the “right” customers about future needs. 

At First Insight, we say: “Data is ubiquitous, Insights are rare.”

Successful retailers are getting the right data into the hands of their seasoned merchants, product designers and marketers – at the right time.

What has your data done for you lately? 

Request a demo to see what many of the world’s leading retailers, brands and designers have found. Value.

Amazon and Anticipatory Shipping – Analytics On the Move

 

Predictive analytics and big data continue to be in a state of flux when it comes to implementation and gaining actionable insights. A recent survey by KPMG revealed a major disconnect among those in the C-Suite, who realize the value of big data but are unsure how to successfully implement and manage the data resources.

We live in an increasingly data-driven world where data & analytics have the potential to revolutionize the way we conduct and manage business operations across the entire enterprise," said Mark Toon, CEO of KPMG Capital. "From CEOs, to CFOs, CIOs and CMOs, the challenge for today's executive is understanding how to draw actionable insights from data and turn them into tangible, genuine results.”

Even though 99% of those CFOs and CIOs interviewed consider data & analytics to be important to their businesses, 75% find it difficult to make decisions using the information.

Why is it such a challenge to draw actionable insights from data and turn them into measurable results? Perhaps it is the fundamental lack of understanding around what your challenges are and addressing them with the right data.  

Amazon Data Ana.com logo RGBalytics on the Move
Jeff Bezos and Amazon have continued to push the boundaries of innovation when it comes to customer service. The “delivery-by-drone” concept is certainly intriguing and takes online purchasing and delivery to a whole new level (we’ll see if it gets off the ground). But it was this week’s announcement of a patent for “anticipatory shipping” that really caught my eye.  

The concept takes data from wish lists, product searches and returns and browsing patterns, analyzes for shopping patterns, and predicts what goods customers will ultimately order. The goods will then be held closer to where the customer lives, reducing shipping time once it is ordered. Bezos wants to ensure the “last mile” the product travels is short and is just as efficient as the “first mile”.

Amazon is using data - lots of it - to strengthen their already-excellent customer service and competitive edge in order to deliver strong shareholder value. Like most successful business leaders, Bezos is never satisfied with the status quo. And although both the drone delivery and anticipatory shipping are still in testing, clearly “business as usual” is not a part of his vocabulary. 

Identify the Challenge – Let Data Do the Work
As I dig further into the KPMG report, this statistic jumped out at me: “56% of respondents changed their business strategy to meet the challenges of big data.” This seems counterintuitive to me. Why? I guess it’s because I see data as a means to address the challenges retailers face, not a challenge in and of itself. If data is the challenge, then perhaps the focus is not on the right challenge the business is facing.

As a former retailer turned analytics junkie, I witnessed first-hand the challenges retailers face. First Insight was started with a question: Why? Why do more than 50% of new product introductions fail? Why do retailers miss the upside on successful products? Why do retailers continue to use the same methods for selecting and pricing new products as they did 20, 40 or even 100 years ago?

This leads me to the reason why the number-one read article in the business section of WSJ.com in 2013 was about Black Friday and the “games” retailers play with discounts and promotions. Although millions of consumers still hold out for Black Friday “deals and door busters,” the number of consumers who live by the motto, “I don’t even get excited unless it is 40% off,” is on the decline. As you may know, the article highlighted First Insight as a solution to these challenges.

The change in what Black Friday means after so many years signals a significant shift in the way consumers shop and therefore how retailers should approach their new product selection and pricing process.  

The Right Data in the Right Hands drives Success
Historical data, surveys, focus groups and conjoint studies are the traditional ways retailers select and price new products. These methods can take a tremendous amount of time, money and human resource to collect and analyze and often times do not yield actionable data that drives results. 

54% of respondents in the KPMG survey stated that their greatest barrier to implementing a data & analytics strategy was an inability to identify what data to collect. At First Insight, we have identified the data that needs to be collected in order to create actionable insights that deliver bottom line results and shareholder value. Engaging the consumer with a more direct and analytical approach is the key to staying ahead of consumer demand. True demand sensing requires a shift in the way you implement the voice of the customer. The right approach takes you from listening to your customer to thinking like your customer.

Our experience has translated into satisfied customers that use our data to ensure they sell more winning products, minimize or eliminate the negative affect of losing products, take advantage of the upside and see data -the right data, - as their ally. 


NRF isn’t about retail. It’s about people.

 

As I walked the hall on Monday morning, it was clear this
truly is “The BIG Show.”Big Ideas Attendance this year was up 8% from 2013, with 30,000 registered attendees – a new record. Eighty-two countries were represented and there were more than 70 delegations from countries such as Brazil, Argentina, Sweden and Russia.

While listening to Matthew Shay, President and CEO of NRF speak about the need for leadership, particularly from the government, my confidence in retail’s representation by NRF with our nation’s leaders was confirmed. Shay stated, “At NRF, we know that our job is to be your eyes and ears – to be your voice – on the most important issues of the day.” Reforming the tax code, opening new markets for American goods, and fixing the broken immigration code so we can welcome new talent are three main areas Shay and NRF are focused on in 2014. 

Switching gears, Forrester’s Sucharita Mulpuru highlighted how successful 2013 was with regards to e-commerce. Average web growth was 29% in 2013, and 2014 promises to be even better. Retailers surveyed for the “State of Retailing 2014” ranked mobile projects such as responsive design, mobile site optimization, and tablet redesign as their top priorities.

With pricing such a hot topic these days, I was intrigued by her comment that “…half of consumers would be willing to pay a premium of 1 to 5 percent in order to get a the product on the spot in the store versus having to wait for an online order.” The death of brick-and-mortar has been greatly exaggerated, and a unique mobile experience along with unique products and assortments “will enhance their chances of their mobile (and in-store) success and create a distinct competitive advantage.”

Former President George W. Bush delivered this year’s keynote. His comments echoed my own philosophy that I don’t want to be the smartest one in the room. Bush stated, “By reaching out I learned that you can learn a lot by listening to someone else. It mattered when it came time to find common ground.” As a CEO, I could not agree more with his statement. Only by listening to others can you truly create an executable vision and strategy that will ensure success. 

The second keynote on day one included Footlocker CEO Ken Hicks. Wearing a pair of Nikes with his suit, Hicks hit on just how demanding the consumer has become. They are demanding because today’s consumer is connected and educated. Hicks was spot-on when he stated, “The customer may enter the store knowing more about the product than the sales associate. You have to be flexible and you have to be aware of what is going on.” Indeed, the consumer is educated, making it even more important to utilize today’s tools and technology to listen and react to what the consumer is saying.

First Insight at NRF – Big Ideas and Breakout Session

As our Big Idea room began to fill before our panel discussion, “How Do You Successfully Price and Forecast NEW Products with No Sales History?” I was amazed at the diversity of the attendees. Retailers, solution providers, equity analysts, professors and students from around the world came to hear our panel speak. 

I asked Mindy Meads, CEO of Calypso, and former CEO of several major brands including Aeropostale and Lands’ End, about new, alternative solutions to introducing new products. “If you are a really smart merchant you’re going to get some help when you can,” she stated. “First Insight has created the algorithms that allow you to improve your track record in deciding what are the top 1, 2, and 3 in the assortment.”

Regarding the importance of optimal opening price points and buy quantity optimization, she stated:“[First Insight] can also help you figure out what price, the optimum price for those new items. I think many times out there we are promoting and don’t need to go so low to get through the season. And the next big one is how do you buy each item. I think that to me is the interesting thing that First Insight can provide.”

TPG Capital Senior Advisor and former Collective Brands and Cole Haan CEO Matt Rubel spoke about tools and big data that enable retailers to speak to the customer and, more importantly, understand them. He commented, “The confluence of big data and what’s going on today and what people want to do to understand their consumer is something that has created big wins over the past 5-7 years.” 

Matt went on to talk about the speed in which testing new products can be done compared to previous approaches to in-store testing.  “The new tools enable us to go out digitally, to set the environment up, to tell the story, to show the garment, to show the shoe, to show the idea and to show it against its competitive set and then to price it. And to play things quite dynamically so in real time what you used to have to spend months to do you now can do in a matter of days and weeks.”

Matt concluded by stating, “There are ways to go about testing what this tool will add to really go in conjunction with the other tools you have. So for me (First Insight) is another great enabler and something we all should embrace very thoughtfully.”

You can watch the Big Idea session by clicking this link. 

During our Breakout Session on Tuesday, our CMO Jim Shea moderated a panel discussion with Helzberg Diamonds and Vera Bradley, where these retailers discussed their experiences and success in applying big data and predictive analytics to fashion. 

Scott Steever from Vera Bradley discussed how they used the First Insight platform to add a level of actionable data to their plan to enter a new market, baby products, in which they had no prior sales history to work from. You can read more about the process and their success here.

I also had the opportunity to attend the 24th annual Financo CEO forum on Monday night, where I heard some excellent comments and ideas on how brands need to adapt, maximize opportunities with their customers and control their own destinies in order to be successful in today’s retail environment. My favorite quote of the evening came from Marigay McKee, the new president of Saks Fifth Avenue. Moderating a panel discussion that included Tommy Hilfiger and Andrew Rosen, CEO of Theory, the question was posed as to whether they thought Amazon would be a credible player in the fashion space in 10 years. Ms. McKee responded, “The successful companies in the future online will be ones who understand how to engage with the consumer, how to talk to them and how to give them what they want. You can’t possibly be living in the world of discounts. It’s not what makes the magic happen.”

This statement sums up my thought mentioned at the beginning of this post: It’s not about retail. It’s about people. I encourage us all to engage them, to listen to them and to seek to understand them…that is what technology enables.

2014 - The Year “Black Friday” Became Irrelevant

 


Black Friday Line

As my 2013 Thanksgiving began to wind down, my thoughts turned to the many conversations and articles written about stores opening on Thanksgiving Day. The buzz around turkey-day openings was much louder than last year. Will shoppers come on Thanksgiving? Will the business cover the cost of being open? Will the tryptophan wear off in time to get me off the couch? But as I wrote in an article on Forbes.com last year titled, “Are Retailers Cannibalizing Black Friday,” Sears, Target, Toys R Us and many other retailers opened Thanksgiving Day, so the practice is nothing new.

However, this year, even more stores opened their doors early, including Macy’s who, for the first time in 155 years, opened their doors on Thanksgiving. For all intents and purposes, Black Friday wasn’t just cannibalized, it was devoured. In its place was a weeklong extravaganza that finds Thanksgiving Day/Evening, Black Friday Weekend and Cyber Monday all rolled into one big, confusing promotional free-for-all. 

The Game has Changed

With Black Friday now fading from view and replaced with this promotional, days-long extravaganza, the traditional approach to measuring the success or failure of Black Friday is no longer valid. Why? There are several factors that make year-over-year comparisons invalid this time around.

First, rather than the one-day, Black Friday event, consumers saw five consecutive days of promotional activity which took the wind out of the Black Friday sails. Second, Thanksgiving fell one week later than last year, shortening the sales window between Black Friday and Christmas. And finally, a rare, once-in-a-lifetime event occurred where Thanksgiving and the first night of Hanukkah overlapped. The last time this happened was 1888. The result was Christmas shoppers with less time to find the perfect Snuggie or gift card, and for those who celebrate Hanukkah, pressure to complete shopping before the 28th. As a result, retailers needed to prepare for the fluctuations in shopping patterns.

The numbers

Here are some statistics from this year’s Thanksgiving and Black Friday:

First, the good news about the entire Thanksgiving/Black Friday Period:

  • According to ShopperTrak, sales for the combined Thanksgiving/Black Friday shopping window increased 2.3% to $12.3 billion
  • Store traffic was also up 2.3% to 1.07 billion according to ShopperTrak metrics
  • According to ComScore, Cyber Monday 2013 sales were $1.735 billion, an 18.4% increase over 2012.

However, on Black Friday itself, the news was not as good:

  • Shopper traffic dropped 11.4% on Black Friday compared to 2012
  • Sales decreased 13.2% on Black Friday according to ShopperTrak

It’s no surprise that sales are roughly flat to slightly up in brick and mortar stores, and online purchases continue to climb sharply. It’s also no surprise that Thanksgiving traffic and sales caused Black Friday numbers to decline.

But I’d like to share some different numbers that, from my perspective, tell a different story about the relationship between retailers and their customers.

Outside the Usual Numbers

Much like stores that start playing Christmas music earlier and earlier each year, the “Holiday” shopping “starting line” continues to move back each year as well (for the record, I was in a store in early September and heard “Jingle Bells”). This year, according to a NRF survey in November, 53.8% of shoppers said they started their Christmas shopping in October. Truth be told, with today’s connected consumer, there is no starting line and for that matter, no finish line.

In addition, according to MasterCard Advisors, 70% of purchases made by consumers during this time were made in the first two stores they visited on that day.   

Consumers are on a Mission

It has become evident that, not just during the holiday season but year round, consumers are focused on finding the best value for their dollar. With holidays, it doesn’t matter when they get the great deal, as long as they get a great deal. And retailers don’t care when consumers make their purchases in the last quarter, just so long as they make them.

That’s why the importance of optimal pricing “outside” of the holiday season is so critical in today’s retail world. When consumers feel like they have received a great value in the spring or summer from a particular retailer, they will be much more inclined to start there during the holidays. 

Retailers that have taken a proactive, strategic approach to ensure the right products at the right price are on the shelf are the ones reaping the rewards and making investors happy.

The bottom line: Delivering products people want at the right price, outside of the holiday season, is the way to win during the holiday season and turn the retailers into the black sooner than “Black Friday”….Opening on Thanksgiving? I can take it or leave it.   


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My Take on the 2013 WWD Apparel and Retail CEO Summit

 

 

 Greg Petro,
CEO of First Insight
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The WWD Apparel and Retail CEO Summit in New York last week was as high-energy as ever. This was my third Summit, and the speakers and sessions were dynamic, insightful and, as promised, “transformational."  The theme this year was how retailers are transforming their businesses to meet the challenges and opportunities of the digital age. 

I also had the opportunity to address the audience at lunch on the first day.  I told the story of walking into my 10-year-old son’s room the previous weekend and seeing a card on his dresser.  It said: “If you’re the smartest person in the room, you’re in the wrong room.”  I told the audience:  “Based on the speakers we have heard from so far, I am clearly in the right room.”

While all the sessions were compelling, a few stood out to me.  The first was a presentation by Dr. Sydney Finkelstein from Dartmouth’s Tuck School of Business entitled Why People Don’t Learn.  Finkelstein talked about how intuition based on experience can be an executive’s worst enemy in times of major change and flux.

“Many of us rely on our intuition based on our experience," Finkelstein said. “When we’re confronted with new situations that are really different, it is possible that our experience can hurt us rather than help us, and that goes completely against the grain of how most people think about experience.”

“All of us have a natural tendency to overgeneralize from small sample sizes,” he continued. “So if you’ve done something once and it worked well, we tend to believe that we can do the same thing again.”

Just a few hours earlier, Eric Wiseman, CEO of VF Corporation, told the audience that he had personally made a $20 million mistake in Japan.  I wonder how many of us would have the confidence to explain to a room full of our peers that we made a big mistake and that it took someone else with a different experience set to fix it?

It is interesting that Finkelstein was talking to a room full of fashion executives, many of whom have relied on their experience and intuition in, among other things, designing and selecting new fashion products.  I could not help but think that Sydney was opening their minds to using other approaches.

Terry J. Lundgren,
Chairman, CEO and
President of Macy’s Inc.
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Terry Lundgren, CEO of Macy's, talked about Macy’s strategy for growth going forward. 

When asked about pricing and promotions, Lundgren said: “You’ve got to start with the product the customer wants.”

“We forecast what customers are going to want six or eight months from now. They identify fashion trends. They have zeroed in on this Millennial customer, and they are right. This is hard, and that is our business — trying to understand what the customer is going to want next season, and it’s not necessarily what sold last season. In fact, it’s rarely what sold last season. That’s forever the challenge of our business.”

“You can have the most beautiful stores, but if you don’t have the right product, it doesn’t matter." A long-time merchant, Lundgren knows that consumers buy products they want, and where and how they buy them is secondary. 

One of the new speakers this year was Nick Robertson, CEO of UK-based Asos.com, the world’s fastest-growing online retailer.  Asos has over 20 million unique visits a day and is targeting consumers in their twenties.  Over the next few years, Robertson sees the business growing to the point where it is evenly split between men and women.  He’s targeting this age demographic since Asos knows young people are spending their money online.  For this age group, in fact, they have found that 40% of their fashion budget is spent online. By the way, Asos is now approaching £1Billion in revenues without brick-and-mortar stores, selling both private brand and branded product.

 Nick Robertson,
CEO and cofounder 
of Asos.com 

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The most interesting part of Robertson’s presentation was his discussion of the rise of “fashion democracy."  For the next generation, he said it will no longer be about what is presented to them on the “High Street."

“The High Street’s presence is being democratized. Twentysomethings have better things to do than go to the High Street. The world’s largest brand is in their pocket [via a mobile device].” 

This is so true. My 21 year-old daughter does not know of a life without air conditioning, power windows on a car, the internet or a cell phone.

Robertson knows that with technology today, consumers will have an active voice in the products that are offered, and this is already influencing Asos’ assortments. 

Overall the WWD Summit was an action-packed two days and has given all of us a lot to think about as we go back to running our businesses. I look forward to your comments and questions.

 

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Greg Petro
President and CEO
First Insight, Inc.  

Science + Art = A Winning Combination Part 3 - Retail

 

In the first two parts of this series, I discussed how the successful convergence of science anddescribe the image art could produce great things. From winning baseball teams to Hollywood blockbusters, industries that have previously shunned technology have seen the enormous value that science and analytics bring to the art of creating innovative ideas and solutions.

As a former retail merchant turned supply chain executive, I have witnessed first-hand the evolution of technology in retail and the positive impact it can have on product selection and forecasting. Walmart, for example, has demonstrated this as it has grown to become the world’s largest retailer through supply chain excellence and technology adoption.

As a retailer, you take risks every day and every season on new products. Your intuition has served you well to get to where you are, but you are one person. As your company grows, how do you scale this capability? And just as importantly, how do you SUSTAIN it? Isn’t that what Wall Street analysts ask every day?

What about those retailers and manufacturers which have not been as successful? What tools are available to help them get on track or help sharpen the competitive edge?

How can you improve your batting average or box office success?

Today, retail executives have access to tools that inject science into the art of design and merchandising. Most of these tools use historical data on existing products to attempt to build forecast models for new products - pricing, inventory optimization, etc. So the idea of using science in retail is not new, but the practice of using historical data to predict new products is, well… history.

First Insight is different. Our solution gathers real-time, forward-looking data on new products. We do this by engaging consumers online, capturing their point of view on a product’s value, applying predictive analytics and giving retailers a forward-looking view on how the market will respond to each new product.  

Don’t believe it’s possible?

Let’s take a few minutes and explore a couple of real world examples: Vera Bradley and David’s Bridal.

In 2012, Vera Bradley was preparing to enter a new product category (Baby). Because it was an entirely new category, they did not know the prices the new products would bear in the market. Utilizing First insight enabled real-time feedback on which products to select and how to price them. Prices were increased on products recommended by the First Insight solution, and the result was an overall increase of 4% in sales above the original plan.

David's Bridal, the largest and fastest growing bridal retailer in the world, was looking for a way to shorten their time-to-market with new gowns.

The entire product introduction cycle was 8½ months and their forecast accuracy was below 50%. The biggest single time constraint was in-store testing, which took approximately 3 months to complete from design to sample delivery in stores. 

Utilizing the First Insight solution, they reduced their in-store testing cycle from 3 months to one week. They also found one of their best-selling gowns of all time through the First Insight solution, which gave them the confidence to more than double the buy. Sales of the dress were 120% of what they originally expected.

You wouldn’t drive a car looking out the rear-view mirror, so why run your business looking only at historical data? 

Putting it all together

Vera Bradley and David’s Bridal are just two examples of fashion companies that have coupled the art of design with the science of product selection and pricing. The science is not a replacement for the art of the merchant or designer - it is an enabler that gives support to their decisions. Trust your instincts and verify with data.

The result: more winning products at the right price points. And bigger bonuses for the merchants.

Baseball… Hollywood… and now Retail. The time is now for data-driven decision-making. Why not see if you can tip the odds in your favor?

 

Science + Art = A Winning Combination: Part 2 - Hollywood

 

 

HollywoodSign

The confluence of science and art has created some of the most significant achievements in architecture, music, sports, and even business.  In part 1 of this series, I discussed the connection between science and art in the world of baseball.  In part 2, I will explore the approach some major Hollywood studios are taking to incorporate data into the art of filmmaking.

Similar to baseball, Hollywood movie production companies risk billions of dollars each year on hundreds of movies across all genres. Very few are blockbusters; many are duds and lose money, and the rest fall somewhere in between. Combining a good script with an “A” list celebrity does not guarantee success. Yet for decades, this was the accepted formula for increasing the odds of producing a winning movie.

As with baseball, Hollywood is an industry steeped in tradition, and the pervasive thinking is that movie production is an art form.  However, with sophisticated investors looking to balance risk and return, “big data” and analytics have found their way into the “back lot”.

So how are Hollywood studios embracing technology to be more profitable and successful? Data and analytics are now being used in two areas: script development and marketing for both movies and T.V. series.

Script writing has long been an artistic craft which many have attempted while only a few have succeeded.  Thousands of scripts have made it to the big screen, and the outcomes of these movies are now known (i.e. blockbuster, dud, or break-even).  Interestingly, each script can actually be broken down into hundreds of attributes.  This is an analyst’s dream – a repository of millions of data points and a known set of outcomes.  How does someone draw conclusions on potential success or failure of a movie script based on all of this data?

Enter Epagogix, a predictive analytics company that places valuations on plot points like car chases, love scenes, location and quirky sidekicks. These factors are scored according to a directory in the way a teacher scores a test. The scores are fed into a computer, predictive analytics are applied and a calculation of how much the movie will make is determined. 

In addition, insight is gained on where changes could be made to increase the earning potential, such as changing the setting or scaling back a role.

The solution was used by a major Hollywood studio to forecast the revenue of 16 new TV shows that would be airing in approximately 3 months. Epagogix analyzed all 16 pre-season trailers to gain insight on their potential success. The shows aired and of the 16, the Epagogix solution nailed 14 of them with regards to viewership and ad revenue.

One Hollywood studio exec said about the solution, “You’re like card counters in Vegas. If you can help us miss just one turkey a year, that would be immense. “

Another area where analytics are being used in the film making business is in marketing.

The typical marketing budget for a feature film is half of the production budget. If the budget is $100 million, $50 million goes towards the marketing effort to fill the seats in the theater. But as is often the case, the production company simply doesn’t know who their audience is or what it could be. The model is antiquated and ineffective in most instances.

One company that is changing the way filmmakers market their art is FilmBreak. Essentially a virtual film studio, FilmBreak empowers filmmakers to actively build, engage, and monetize their online audience. Prior to release, filmmakers can quickly and easily promote their films through social media, build a fan base, and incentivize fans to support their films by offering access to exclusive content, live stream video chats and production updates, as an example.

FilmBreak helps filmmakers figure out who their audience is and learn about their taste profiles. The data they collect helps them optimize their marketing effort so their marketing dollars can go further.

Similar to baseball, rather than using data to take away from the creative magic of screenwriters which has been trusted for decades, the goal is to make the production more merit-driven based on verified information, not on somebody’s opinion or connections. 

So far we have explored the practical applications of combining science and art outside of the retail industry. In my final post in this series, I will discuss how the right mix of science and art is changing the way retailers design and select new fashion products, mitigating the risks of new product introductions.

Science + Art = A Winning Combination

 

Part 1 - Moneyball   art & science

Left-brain vs. right brain.  Logic vs. emotion.  Science vs. art.  For centuries, we have assigned people and their thought processes into one category or another. But does is it really need to be one or the other?

There are many examples throughout history of how artistic talents have been married with specific scientific skills to solve complex problems and create wonderful things: the great pyramids, the works of da Vinci, the Roman Coliseum, Machu Picchu and the Pantheon are just a few. The most successful people, cultures and business have found the right mix of the two. 

In modern times there are equally impressive examples of the marriage of science and art. In this three part series I will explore this dynamic across several industries, concluding of course with my favorite – Retail. By the end I hope you will agree with me that the most money can be made when applying science to artistic endeavors.

My fellow merchants – Please stick with me as I present this topic and set the stage for the next generation of science and art in retail. It will be well worth the read.

First let’s start with baseball.

Moneyball

Suppose you ask a friend how much change they have in their pocket and they respond, “eight coins.” Would you think you had learned much about the exact amount in their pocket?

Compare this to determining a player’s batting average where you divide the number of base hits by the total number at bats.  Does this tell you much about what actually happens on the field? In other words, it doesn’t tell you how the baseball team scores runs, gets outs and wins games.

In both examples, the measurements do not answer the real question being asked. In these questions lie the foundation of sabermetric thought.

Popularized through the book Moneyball and later in the movie starring Brad Pitt as Billy Beane, the term “sabermetrics” is derived from the acronym SABR, which stands for Society for American Baseball Research.

Baseball is, and always has been, a numbers game. Since its birth in 1845, baseball and numbers have been inseparable. Baseball has also tried very hard to maintain its “old school” mentality when it comes to changing rules or processes for the betterment of the game. For example, we still have umpires making judgment calls on balls and strikes when a computer could easily make accurate calls instantaneously.

Each year, teams invest millions of dollars in players –both new draft picks and free agents –at the risk of one or many of them not performing up to the level needed to win. For the first 150 years of baseball, scouts would look at the traditional statistics – batting averages, RBIs, stolen bases and ERAs – used to determine the potential for each player and a corresponding dollar amount they were worth.

So it came as no surprise that when the sabermetrics concept started to gain traction in the world of baseball, the traditionalists were not impressed. For many, there is no reason to view the game through such a complicated lens. They felt the game should be experienced and analyzed as it always has been, and reducing the game to a binary code would detract from the true essence of baseball.

But a funny thing happened on the way to the ballpark. 

The merging of science and art is often born out of the need to solve a problem. For the Oakland A’s in the late 1990s and early 2000s, the problem was money. Under new leadership, the team salary was slashed to a level that gave the A’s the third lowest payroll at approximately $40 million. In contrast, the Yankees were at the top at $126 million. With no salary cap, how does a team at the bottom of the payroll ladder compete against a team at the top?

Enter Billy Beane and sabermetrics.

Beane, a former player and now VP and General Manager of the Oakland A’s, studied and adopted the concepts behind sabermetrics in an effort to find value in players that would have otherwise been passed up. Beane applied predictive models to non-traditional stats like on-base percentage to determine the player’s value.

Beane looked under the rug and found value in players who were passed up based on traditional statistics. The result? They reached the playoffs in four consecutive seasons from 2000-2003. In 2002 they became the first team in over 100 years to win 20 consecutive games.  Given that the A’s did not significantly increase their payroll during this period, I‘d say this was a very successful, non-traditional use of statistics to solve a challenging problem.

The model used by the A’s has now been adopted throughout baseball.  However, even though analytics were brought into the process to validate the scouting, the scout is still trusted for his role in identifying candidate new players who could be a fit for the team and its culture – which is more of an art.  It is this blend of art and science that has been adopted throughout baseball.

The end result is efficiency - identifying more “diamonds in the rough” and fewer busts. At First Insight, we apply a very similar process to finding winning products for the retail industry.  The designer and merchant are experts in the art of setting trends and identifying candidate new products.  First Insight adds the science of predictive modeling to determine which items will be the winners and how to price them.

In my next post, I will look at how Hollywood has adopted a similar approach – applying science to the artful craft of movie making.

Demand Sensing Turns Traffic into Conversions

 

For the quarter ending July 2013, Thomson Reuters put the average comp sales gain among reporting retailers at 1.9%, which is relatively flat compared to Q2 2012. Here are Q2 comps reported from several retailers:

  • Macy’s – Down 0.8%
  • Walmart – Down 0.3%
  • Urban Outfitters – Up 9% 

Top performers for the quarter included home improvement stores which are benefitting from a stronger housing market. Leading the way were Home Depot, up 6.9% and Lowe’s, up 5.3%. 

Department stores saw smaller gains with an average comp increase of 2.6% across the category, with Nordstrom on top at 6.7%.

And although purely an online play, Amazon continues its upward momentum. Online sales still make up a small percentage of overall sales, but the upward trend in e-commerce is having a stronger impact on revenue for those retailers which have put their full weight behind e-commerce vs. those which have not committed to an omni-channel strategy.

That said, why are some companies increasing comp store sales and others are not?

First, let’s consider the metric of Comp Store Sales.

Why Comp Store Sales?

Year-over-year comp store sales is the de facto measurement used to track retail growth as it eliminates incremental new store sales and accounts for seasonality.

But to increase comp store sales, at least one of two key factors must increase: store traffic and/or the conversion rate of shoppers.

As I read through the spate of disappointing earnings, particularly among teen retailers, one element was consistently cited as a contributing factor to poor earnings and comp store sales: store traffic. Yet, according to ShopperTrak, shopper traffic in retail stores and malls was up 6.9% in May 2013 vs. May 2012, flat in June 2013 vs. June 2012 and down 2.3% in July 2013 vs. July 2012. Although traffic is starting to trend downward, it is not as precipitous as the downward comp sales trend reflected in recent earnings calls.

If in fact mall and store traffic is declining, what can retailers do to increase comp store sales?  

The answer is simple. Convert more of the customers that are coming into the store into paying customers. After all, not all retailers announced declining comps for Q2, so some are clearly converting at a higher rate and are gaining share. 

Although conversions are critical, according to Retail Customer Experience, only 35% of retailers track conversion rates in their brick-and-mortar stores. Calculating conversion rate is simple: Divide sales transactions by the number of people that came into the store. If you count 200 people coming into the store and 100 transactions, your conversion rate would be 50%. 

Poor conversion rates can be attributed to a number of factors including inadequate staffing and long lines at the checkout counters. However, the two primary contributing factors to low conversion rates are out-of-stocks and poor merchandising. If you don’t have enough of the winning products, or never had the right products to begin with, your conversion rate will always suffer.

Turning traffic into conversions

Understanding why people don’t buy is difficult to ascertain. However, it is clear that many customers are leaving without buying because the store simply didn’t have the products they valued.

Adjusting inventories to reduce out-of-stocks and filling the floor with the right products is no longer a guessing game. It can be done in near real-time to impact existing products and to make future buying and merchandising decisions. 

First Insight can help you understand how to run your business in anticipation of what the market is going to do…not to react to what’s already happened. 

When you think like your customers by listening to them, more of the traffic will convert from browsers to buyers. 

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