Drive ROI With Distributed Analytics

The data challenge

According to Accenture, the volume of big data hatched by business is more than doubling every 1.2 years, and merchants are in a race to monetize this deluge of data being generated throughout the retail ecosystem.

And while mounting megabytes of data might make retailers’ heads spin, the savvy analysis of that data is a potential windfall: The McKinsey Global Institute estimates that retailers leveraging data analytics at scale can grow profits by a whopping 60%.3

But doing so is easier said than done. Hobbled by legacy systems, many retailers are ill-equipped to offer real-time visibility into product demand and pricing trends, and measure how store operations impact the overall shopping experience on a store-bystore basis.

A retail network starved for distributed analytics lacks granular, up-to-the-minute insights on customer buying behavior and demographic trends; lacks the ability to convey this critical information to its store operators, brand partners and advertisers in real time; and thwarts inventory management optimization to deliver the right product mix to the right store at the right time — the holy grail of retailing. The result is lost sales, lower profit margins and untapped revenue streams.

1. Better visibility into local customer buying patterns and preferences

Amazon’s product recommendation engine — the “if you bought that, you might like this” feature — raised the bar in how retailers analyze consumers’ shopping baskets. The online shopping innovation, powered by Amazon’s proprietary algorithms, accounts for 35% of Amazon.com’s revenue, which underscores the critical and growing role data-driven insights play in driving retail sales.

From POS information and in-store traffic to social media, review sites, inventory analytics and countless other sources, retailers are generating more data than ever before, which can be used to gain unprecedented insight into customer behavior. But despite this wealth of data, one of the key challenges they face is the difficulty in gaining clear visibility into overall organization operations, revenue forecasts and customer satisfaction due to disparate systems and lack of streamlined reporting.

Consolidating all of the information from these various sources into one place is essential, but it’s only one piece of the puzzle. The real value comes into play when you gain the ability to distill these strategic insights from across your retail business network and then get that information into the hands of the managers, operators and suppliers that keep your business running.

• Case in point

Market basket analytics technology paired with distributed analytics can bring newfound scale and accuracy to the retail modeling method. This is achieved by giving every level of your retail network, from corporate executives to buying managers to suppliers to individual store managers, unprecedented visibility into what items shoppers typically purchase, as well as where and why they purchase those items, allowing your brand to better adapt to and harness these local trends.

The insights gleaned from data analysis and distributed analytics can maximize product placement in all types of stores. The diapers-and-beer buying scenario is now a classic, go-to example of how retailers can capitalize on shopper buying patterns by harnessing insights from data analytics. By analyzing data from multiple touch points, such as point-of-sale and loyalty card data, a mass merchant was able to identify the purchasers to be men, who, when buying diapers for their babies, often bought beer, too.

The lesson is that self-service data analysis can unearth unexpected insights that lead to new ways to maximize consumer purchasing trends. Cutting edge distributed analytics let you take this lesson one step further, as rather than make adjustments to inventory on a strategic level, these can be made at the store level for maximum impact as these stores understand their unique markets (i.e., stores in Napa Valley may see similar increases in cabernet sauvignon purchases instead of Miller Lite).

For example, Firehouse Subs was able to distribute insights to its 915 locations via a standardized set of KPIs and dashboards, enabled when the brand partnered with GoodData to create its “Station Pulse Analytics.” The business impact of sharing key learnings throughout its franchise network brought nearly immediate results: within six months, Firehouse Subs achieved:

• 8% increase in overall “scorecard” grade
• 3% increase in overall customer satisfaction
• 2% increase in overall quality of food

These improvements contributed to millions of dollars worth of revenue increases; this is what we mean when we talk about data ROI.

2. New revenue opportunities with supplier partners

As many as 89% of companies tapping into big data are doing so to create new products and services. For retailers, the right analytics can pave the path to new revenue streams both for them and their supplier partners. Indeed, for retailers, insights gleaned from shopper purchasing patterns and product performance provide the rich raw material for untapped merchandise opportunities, either to fill a category void or target a forgotten demographic.

Now business intelligence gleaned from analytics tools — rather than an Excel spreadsheet and gut instinct — is taking data monetization to new heights.

These days, retailers and suppliers can share a single view of the same merchandise data, including key metrics such as seasonal past performance and promotion results, to collaboratively identify new revenue opportunities. These can include offering suppliers aggregate market or competitive data in order to better inform pricing decisions.

• Case in point

A department store chain noticed that sales of its largest women’s fashion brand had leveled off. Working with the vendor partner, the team evaluated data from multichannel purchases, demographic profiles and insights culled from social channels, such as Pinterest “pins,” to identify a key shift: The brand’s core shoppers had become more health-and-fitness conscious, and were now in search of casual fare, including athleisure wear, while the brand’s assortment heavily skewed toward workwear looks. With this new insight, the apparel brand and department store co-created the spin-off “FashionSport” collection to address the void, generating a new revenue stream to drive ROI.

3. ROI analysis of social and mobile campaign strategies

Social media has become an invaluable way for brands to take the pulse of their customers, who increasingly live their lives on these networks, spouting their “likes,” dislikes and unfiltered opinions on stores and the brands they carry.

Retailers are keeping abreast of social chatter via “social listening” analytics tools to spot trends, gauge what products are flying or flopping, follow what social influencers are saying about their brand, and monitor competitors.

• Case in point

Target leverages “social sentiment data” — insights gleaned from promotions across social networks — to monitor how shoppers respond to its signature designer collaborations, Forbes reported.

But tripped up by disparate digital data sources and dubious data integrity, Target was struggling to measure the revenue impact from its social channels. Using GoodData’s social media analytics expertise, the hip discounter was able to combine data from eight different social sources to unearth a comprehensive picture of its social media marketing efforts, which offered visibility into share of voice, brand health, product and channel audience matching and traffic contribution.

“With GoodData, we’re able to see in one place how social media impacts Target’s revenue,” said Grant Olson, the retailer’s Marketing Manager of Social Media.

Target, like Firehouse Subs, realized that actions must be local, and therefore using a distributed analytics platform to inform each store is the key to overall revenue improvement.

4. Ability to track and evaluate the entire omnichannel shopper journey

While data collection from online shopping is a standard practice, retailers are moving to the next level of analytics tools that combine information from shoppers’ e-Commerce footprints with point-of-sale transactional data, along with customer demographics from local retail stores.

The idea is to capture a single 360-degree view of today’s multichannel shopper to inform smart merchandising and marketing decisions. Retailers that don’t get this right are leaving money on the table: Multichannel shoppers, whose ranks are growing, spend more than single-channel shoppers.

Understanding customers’ seamless, omnichannel expectations can be summed up like this: “Know Me, Show Me You Know Me, Enable Me and Value Me,” according to the Accenture report 'The New Omnichannel Approach to Serving Customers'. “Customers want the service provider to know their personal profiles, including devices, services and content purchases.”

Distributed analytics tools are designed to do just that by offering both visibility and data-driven intelligence on consumers’ in-store, online and mobile shopping footprints, which is critical amid the growing popularity of “click-and-collect” options like buy online, pick-up-in-store.

• Case in point

Retailers need to have access to cross-channel data to help them target shoppers with the right messaging at every touch point. And they need to be able to access that data down the line.

For example, if Mary reacts to an online promotion on Facebook, then starts researching a product on her mobile phone during lunch, then goes back to work and looks at the brand’s e-commerce site, and then visits the store after work, the store associate should be aware of Mary’s activities prior to when she entered the store so she can direct Mary to the item, provide her a relevant offer on the product she’s interested in, and suggest accessories or similar products that might be good cross-sells or upsells. Then, post-purchase, with all the data in hand, the retailer follows up with a thank you and makes sure not to try to sell Mary the same product she already bought.

5. More effective targeted promotional campaigns and personalized offers

The Internet is now the world’s largest store, offering an endless aisle of products, services and experiences for every conceivable taste and interest. To that end, “individuals are able to personalize and express themselves through their consumption to a greater degree than ever before,” and at cheaper prices than ever before, according to a report by trend forecasting firm TrendWatching.

Today’s shoppers are shifting away from one-size-fits-all merchandise to personalized, customized goods that reflect their distinct DNA. For example, logo-driven apparel and accessories brands are suffering, while sites like ModCloth are on the rise. At ModCloth, shoppers are invited to help select the design or product that gets sold on the site.

• Case in point

Personalization has been woven into all facets of Nike’s business, from product design with items like HyperAdapt 1.0, a sneaker that uses internal mechanics to instantly adjust to a user’s foot, to customized shopper engagement features informed by analytics.

The sportswear retailer’s app features a personalized newsfeed of products as well as training tips based on a user’s workouts and preferences, leveraging what’s being called “dynamic content targeting,” content based on a shopper’s behavior and context.

6. Optimal pricing strategies by SKU, location, and region

These days, the price had better be right. Merchants are faced with serving consumers who compare retail prices on the go from their mobile devices, revealing both good deals and rip-offs in real time.

To complicate matters, legacy chains are competing with online retailers’ pricing prowess. E-Commerce merchants are armed with sophisticated analytics technology equipped to instantly make thousands of price changes, a practice that’s now commonplace in the dynamic pricing environment born from online shopping.

To that end, forward-thinking retailers are trading up to priceoptimization platforms that monitor purchasing patterns for products by price and time of day, and quickly make price changes to respond to market conditions and buying shifts.

Case in point

When the price wars heated up in the supermarket space with the rise of smartphone comparison shopping, a national grocery chain upgraded to a price-optimization platform that tracked the pricing and customer demand on thousands of SKUs, then analyzed the data to offer weekly price recommendations. The supermarket’s phased out spreadsheet-based method could not have handled the task. The upgrade ended up boosting gross profits at the grocery chain, in part by identifying products ripe for margin optimization.

7. Benchmark data on location-specific performance to improve the customer experience, loyalty, and overall revenue

If “all politics is local,” the same can be said about retail. The ability to track how store operations impact the customer experience, loyalty and revenue on a local level is integral to optimizing product assortments, marketing and supply-chain efficiencies.

• Case in point

Restaurant chain Firehouse Subs struggled to gain location-specific visibility into key performance metrics such as sales, Yelp ratings and customer-satisfaction results at its 915 franchised locations.

The chain turned to GoodData to devise a restaurant performance dashboard, an all-in-one analytics tool that combined data sources such as sales, operational metrics and customer satisfaction results to provide a whole picture of each restaurant’s performance. Firehouse Subs could then dive into the data via numerous dashboard tabs such as the “scorecard” tab, which calculates key performance indicators like the restaurant’s average weekly sales performance benchmarked against goals set by the parent chain. The dashboard also features a sales tab that measures the impact of weather conditions on sales performance.

With the GoodData platform, “We are able to distribute analytics to our more than 915 Firehouse Subs restaurants with a scorecard grading 10 key metrics,” said Danny Walsh, Director of Reporting and Analytics for Firehouse Subs. “This awareness helps sales performance, guest satisfaction scores and being proactive during downturns, and improves franchise efficiency.”

But the proof is in the bottom line data ROI: The platform boosted the chain’s scorecard grade, customer satisfaction and food quality by 8%, 3% and 2%, respectively, according to GoodData.

8. Improved operational efficiencies and reduced operational costs

Retailers are turning to data analytics to optimize operations, the less-than-glamorous yet essential nuts-and-bolts of retailing that ranges from inventory control to facilities management.

According to a study by the McKinsey Global Institute, retailers that leverage big data can increase their operating margins by a hefty 60%.

• Case in point

Facilities management firm ServiceChannel operates a SaaS platform that streamlines the management of people, processes and buildings at more than 100,000 external locations, including malls and retail chains. The web/mobile work order management platform handles tasks ranging from managing labor and suppliers to finding qualified contractors.

Seeking to up its value to “information hungry customers” like the Gap and Burlington Coat Factory, the company partnered with GoodData to enhance its facilities management platform with embedded advanced analytics. With this move, ServiceChannel now arms facilities managers at retail chains with scorecards and dashboards that measure contractor performance and enable cost visibility across their enterprises, evaluating metrics such as HVAC repairs and weather-related causation metrics.

The platform has massively helped drive data ROI: Retail clients have reaped the rewards of greater visibility into repair and maintenance, along with reduced operating costs and compliance risk, according to ServiceChannel.

9. Reduced out-of-stocks and overstocks through real-time inventory data

It’s Retailing 101, but inventory management efficiency is a cornerstone of a successful retail operation. Getting this wrong can cost retailers a bundle: Overstocks and returns are costing retailers $1.75 trillion a year, CNBC reported.13

Retailers are tapping distributed analytics to enable data-driven inventory intelligence across the organization, from corporate headquarters to district store managers and suppliers. These realtime inventory management platforms enhance visibility into sellthrough rates to avoid both empty shelves and excess inventory; thwart excessive markdowns; optimize a retailer’s SKU mix; and enable merchants to nimbly adapt to dynamic market demands.

• Case in point

After implementing a supply chain optimization platform that analyzed historical merchandise buying data and forecasted temperature trends, a home-improvement chain was able to stock shelves with laser-like precision, calculating which consumers in disparate regions of the country would need snow shovels, and which ones would need beach umbrellas.

10. Improved employee motivation and satisfaction

Healthy competition can boost employee engagement, just as working toward a goal is known to increase worker satisfaction. Indeed, opportunities to use skills and abilities is one of the top three factors that contribute to job satisfaction.

• Case in point

Firehouse Subs found new ways to motivate employees after installing its restaurant analytics program. The platform included the benchmarking comp store sales/transaction tabs, which rank a franchise or franchise owner against indices such as year-overyear comparable sales transactions and average check. The chain discovered that benchmarks could be a powerful motivator: As franchisees could easily track their performance metrics against others in the chain, the platform incentivized improvements, upping employee motivation in the spirit of competition and in the pursuit of excellence.

Who are Retail TouchPoints?

Retail TouchPoints, who partnered with GoodData to create this ebook, is is an online publishing network for retail executives, with content focused on optimizing the customer experience across all channels. The Retail TouchPoints network is comprised of a weekly newsletter, insightful editorial blog, special reports, web seminars, exclusive benchmark research, and a content-rich web site featuring daily news updates and multimedia interviews at www.retailtouchpoints.com.