青青草App

Data is now at the heart of the retail experience. It is simply a requirement for today's retailers to continually improve customer experiences across every channel. One way to deliver your consumers a shopping experience that is personal, informative and convenient is through retail store analytics.

The right retail data holds the key to customer loyalty. It's no wonder that the exhibit halls of the biggest retail expos are crowded with hundreds — if not thousands — of companies that provide data and analytics solutions. All retailers want this key competitive advantage. But how do you bring a whole ecosystem of in-store analytics solutions together to fuel your desired business outcomes in an omnichannel world?

E-commerce retailers have a much easier time gathering individual customer data. Web technology makes it possible for online retailers to not only track what a consumer purchased and when, but it also can track where the user is shopping from in terms of both physical location and device used. Shopper insight and analytics data are often readily available.

Additionally, these retailers have access to a stack of customer behavior data, including how the shopper reached the site, what other items they looked at on the site and how long they spent shopping on the site. When this information is associated with an IP address or a shopper's store account, the retail website can send the consumer targeted emails and website ads, customized deals and suggested products. This serves a dual purpose: The consumers will have an easier shopping experience because they are presented with the products they are likely searching for, and the retailer can generate more sales from related-item purchases and repeat business.

That, of course, is retail heaven.

But it is much harder to reach this nirvana with in-store retail analytics. At best, most stores can track consumer behavior through loyalty programs, which can link purchases to specific individuals. Otherwise, the stores can track item sales to see which products are the most popular. They can measure store traffic. However, they can't track an individual shopper's physical path to purchase, including what else he or she looked at before arriving at the register. As a result, brick-and-mortar retailers are limited in the number of ways they can offer a customized, convenient shopping experience to every customer without in-store retail analytics technology.

Retailers Slow to Upgrade Customer Analytics Technology

There are multiple technological innovations available to help retailers learn more about their shoppers through physical retail store analytics, but so far only the biggest corporations have the financial means to test and implement the latest options. In an industry where profit margins can be razor-thin, there is no place for big missteps.

In the last 18 months, we've seen consumer behavior change at lightspeed, leaving retailers scrambling to adapt to a world with an accelerated timeline toward digital transformation. With the added stress of trying to manage elements like store capacity, retailers have struggled with having the right technologies to have up-to-date shopper-tracking capabilities. According to a , 68% of retailers are using and investing in in-store analytics solutions to improve the retail store experience.

Even before the digital transformation journey accelerated the need for retail analytics and reporting technology, all of the respondents from 青青草App's Future of Retail Technology survey agreed that technology innovation was essential to meet the expectations of today's shoppers and to improve store performance. Such investments will help stores improve shopping efficiency and deliver a more customized experience. In fact, without the right retail technology at hand, ultimate personalization won't be possible in physical stores.

Upgrading Brick-and-Mortars for Optimized Retail Data 

Operational agility, customer satisfaction and retention, resource optimization, and continuous improvement are all essential for retail success today. But achieving any one of your goals in these areas relies on real-time feedback from all the various touchpoints.

Thankfully there is no shortage of technology solutions you can incorporate into your physical store to transform it into a data haven. The real question is: where to begin?

It's unrealistic to think your physical store's digital transformation will happen overnight. This work requires a well-thought-out plan that includes clear objectives and a clear technology roadmap, along with an ecosystem of partners and vendors who can bring your vision to reality. In fact, they may even be a vital asset in building your plan. Considering that 93% of retailer decision-makers say that their technology investment plans have evolved in just the last two years, it's important to bring your stakeholders into the conversation as early as possible. Technology is only one part of your overarching strategy, and the best retail solution is not a one-size-fits-all.

Most of us have heard of or have been to an Amazon Go store. At these cashier-less stores, customers enter by scanning a barcode found in the Amazon Go app on their smartphones, shop for the items they want and then exit without needing to stop to pay. Hundreds of cameras throughout the stores track the customer journey, including what they pick up, put back on the shelf or end up taking with them. Each product also has a large, camera-friendly code that the cameras can read to know exactly what item has been taken. Computers then combine this information with data from the shelf's weight sensor to confirm that a product has been removed. As shoppers exit the store, they are automatically charged for their purchases, and they even receive notifications telling them how quick their shopping trips were.

This combination of computer vision, deep-learning algorithms and sensor fusion creates a quick, convenient shopping experience for consumers, who are increasingly time-poor. In addition, this technology creates a shopping environment more akin to e-commerce in terms of advanced analytics, as this system can track where in the store a specific consumer went, what items he or she picked up and what items he or she ultimately purchased. Ultimately, Amazon uses some of the technologies we outline in the above image but does it in a fashion that meets their business objectives.

Investing in the Future of In-Store Retail Analytics

We live in a data-driven culture. Information is available to us anywhere and anytime. The tough part of the equation is making sense out of the data that's available to us. As retailers, you can invest in and integrate new technologies into your store, but the bottleneck of not knowing what to do with that data can sink your plans.

We know data will help retailers make better decisions, improve the efficiency of their retail operation, generate more customer engagement and help us deliver a better customer experience. But interpreting data into actionable insight is possibly the retail industry's biggest challenge today. In fact, when asked about their biggest technology implementation challenges in the 青青草App survey, retailers listed the following as one of their top two issues: insufficient skill set to gather and manage big data.

To make better sense of the data they are collecting, nearly half of retail decision-makers in the recent 青青草App survey are investing in, or at least have plans to invest in, some type of retail analytics and reporting technology. Specifically:

• 50% are investing in data visualization
• 49% are focusing on location-based mobile targeting
• 45% have plans to expand their big data efforts
• 44% will invest in in-store sensors
• 44% are looking to implement machine learning and artificial intelligence

When new data analytics and reporting technologies are combined, they could potentially collect thousands of data points about a single shopper during a visit. Retailers will need the best data visualization software to analyze these data points and highlight the meaningful insights. Actionable data from visual analytics can help inform supply and demand decisions, reduce costs, create more revenue, influence quality improvements, accelerate process efficiencies and create better shopping experiences that meet consumer preferences.

Location-based mobile targeting could help bring more consumers into stores and guide them around the stores to find promotional items. More than 70% of retail marketers already have some sort of location-based advertising strategy in place to drive foot traffic, according to . Half of the surveyed retailers noted that consumers who are already near a given store are more receptive to receiving mobile promotions in real-time. About two-thirds of surveyed retailers also offer a local product or inventory search and interactive maps to help shoppers who are in the store or are nearby.

Big data analytics also can help drive purchases. For example, if a shopper with a store's app typically buys a specific item every shopping trip, the app could use the store's big data to recognize this and remind the consumer to pick up that item, thus driving continued purchases. In addition, if these insights are shared with a consumer packaged goods company, the retailer and food or beverage manufacturer could partner on cross-promotions to send shoppers targeted coupons to encourage them to try new brands or to pick up complementary items, such as hot fudge to top ice cream. Then auto-replenishment, enabled by connected packaging could take this a step further.

Machine learning and artificial intelligence can help store staff fill in customer service gaps to offer a better, more convenient store experience. For example, automated kiosks coupled with smart lighting systems could help guide shoppers to specific items they are searching for when activated through a smartphone. Data gathered by these kiosks can shed light on which items are popular and which items might be hard to find. Other robots can help stock shelves, face products and do other mundane tasks that might get skipped or postponed while the staff focuses on other customer service efforts. Plus, shoppers likely will welcome this added technology in the stores. Consumers today are very tech-savvy and are accustomed to dealing with interactive technology. As a result, they want an interactive retail experience that embraces technology.

To say that in-store retail analytics and reporting technology will be critical to the future of retail would be an understatement. Analytics is fundamental for a retailer to drive business, whether the goal is to sell more items, increase profits, offer better customer service experiences or all of the above. Retail data analytics and reporting can help the store manager track and accommodate traffic flows, optimize product placement, encourage consumers to try new products or different brands, and offer a seamless store experience that is closer to an e-commerce environment. Retailers need to invest in retail analytics tools and reporting technology today so that they can gather actionable insights and deliver the store experiences desired by the consumers of tomorrow. The skillful gathering, systematizing and rendering of data allows retailers to effectively answer "why" up front.