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<\/p>\nConsumers accustomed to the autonomy of online shopping are often disappointed when they walk into physical stores, only to find that a retailer hasn\u2019t updated its store experience to match new digital-inspired shopping habits.<\/p>\n
Online, these shoppers are used to being able to find what they want \u2014 in any variation they want it \u2014 as well as get answers to any questions they have, nearly instantly. They now expect similar tech-enabled conveniences when they head into stores they love. After all, despite digital shopping\u2019s benefits, physical stores are still the only place they can touch, feel, test out and take home their purchases all on the same day.<\/p>\n
Despite the benefits of in-store shopping, many retailers have seen their models threatened by digital technologies \u2014 but only because they haven\u2019t adapted to them. Now, these retailers are bracing themselves for the next wave of digital\u2019s evolution as those perceived threats are further enhanced by artificial intelligence.<\/p>\n
Rather than sitting this one out and risking a deeper disconnect with customers, there are a number of emerging, yet very practical, digital and AI use cases that can be easily put to work in stores to increase profitability.<\/p>\n
Here\u2019s a look at three of those that even the most analog retailers are putting into place to create an experience that resonates with today\u2019s more digital-savvy shoppers.<\/p>\n
1. Personalize customers\u2019 shopping experiences in-store just like online retailers do.<\/strong><\/h3>\nOnline retailers have mastered the art of tailoring shopping experiences to meet the individual preferences and behaviors of each person on their site. For instance, anything that a shopper searches, clicks on and buys on Amazon.com further informs the marketplace\u2019s understanding of them \u2014 both in the moment and over time. Whether a shopper has been on the site one time or a thousand times, Amazon uses what it learns to automatically serve up recommendations that complement what it knows about the customer’s current and past shopping activities, size, styles and tastes, all in effort to increase the order value right then and there.<\/p>\n
Because this type of digital shopping experience has become the norm across digital retailers, consumers have come to expect this sort of personalization everywhere. However, how do you translate this experience in-store for customers who are willing to spend more if they\u2019re just pointed in the right direction?<\/p>\n
Digital platforms in aisles are one answer. Installed throughout brick-and-mortar stores, digital self-service options empower customers to browse and find what they\u2019re looking for \u2014 whether it\u2019s in the current store location or not \u2014 and provide portals through which retailers can begin logging customers\u2019 preferences and shopping habits to build out those same types of profiles as online.<\/p>\n
Where AI comes in is turning the insights gained about each customer into personalized recommendations that are served to the customer right then and there, and which become more precise over time. And it can do it at scale, meaning it remembers each shopper that interacts with the platform, each subsequent time they use it, and tailors its recommendations to account for all new information it gathers.<\/p>\n
This approach lets retailers go from having no digital experience in-store to having an AI-enabled self-service tool that feels familiar to shoppers, and which marries the ease of online shopping with the tangible advantage of being able to see different products in person at physical stores.<\/p>\n
2. Incorporate AI-powered sales staff in-store.<\/strong><\/h3>\nStores across the board are navigating staffing challenges \u2014 ranging from not having enough staff to not being able to keep the staff they do have fully educated on their large product offerings. These issues can directly translate into customers either leaving without finding what they need or simply buying what they came in for \u2014 and nothing else.<\/p>\n
Everyone in retail knows that upselling is the key to increasing order values. And customers are often willing to buy more than initially expected with just a little bit of prompting. However, human sales associates aren\u2019t perfect and get pulled into a million different directions during the course of a work day. Additionally, retailers have anywhere from hundreds to thousands of SKUs in stock and not even the most veteran store staff know every detail about each one. This makes it difficult for staff to make the best recommendations to the customers they do help.<\/p>\n
Digital platforms in the aisle can step in when these shortcomings are present, enabling shoppers to find products, get information they need, and discover products they might not have otherwise stumbled upon.<\/p>\n
Digital can even complement sales staff who are trained to navigate it, using it as a sales aid to answer complex questions and ultimately ensure the sale. AI can then step in to take that sale a step further by using what customers are currently doing and creating themed bundles based on data-driven insights. For example, a shopper in a hardware store is looking for a paint brush. AI imagines a larger painting project and automatically suggests painter’s tape, spackling paste, sand paper, paint thinner and protective sheets to cover the floor. It might even further show them a bundle of all of these items at a slightly reduced price.<\/p>\n
In this case, AI acts as an extra salesperson \u2014 one who never needs to take a break, never forgets to upsell, and will remember the customer every time they come in again \u2014 all with the purpose of increasing customers’ basket sizes, loyalty and value over time.<\/p>\n
3. Understand what inventory shoppers want in each location and how to merchandise it to increase sales. <\/strong><\/h3>\nUnlike their online counterparts, physical retailers have finite space to show all of the inventory they carry. This results in both direct costs and opportunity costs, such as the price of losing a customer when they can\u2019t find what they want or missing out on a chance to sell them more because they can\u2019t see everything that\u2019s available to them.<\/p>\n
Now there are multiple options to circumvent inventory restrictions in stores. Digital platforms, for instance, can help show the entirety of what a retailer has to offer, even when the products or sizes they want aren\u2019t available in-store. This alone can ensure that an engaged shopper doesn\u2019t leave the store without buying.<\/p>\n
As more shoppers use these platforms, they begin gathering information about what customers across the board are looking for in each store location and where there’s demand \u2014 or not \u2014 for different products. AI can then synthesize this data to optimize inventory management, predict what products and sizes should be featured in each store, and which would be best reserved for online or other sales channels. It can also tell retailers which products are the most popular and which are commonly considered or purchased together. All of this can inform exponentially more lucrative merchandising decisions.<\/p>\n
While retailers already have years or decades of sales data they could conceivably reference to understand these types of sales trends, it’s next to impossible to analyze these transactions manually, come up with actionable insights, and then turn those insights into a tangible merchandising plan. With AI, doing exactly this is table stakes.<\/p>\n
Looking Ahead<\/strong><\/h2>\nMany physical retailers have approached technology as a threat, but technology and brick-and-mortar aren\u2019t at odds. In fact, with the introduction of digital experiences, stores can offer everything that digital shopping channels do \u2014 with the added benefits that in-person experiences offer.<\/p>\n
Even retailers that have never considered doing anything<\/em> with digital can quickly get ahead of competitors \u2014 online and offline \u2014 by considering these practical ways of putting AI to work. After all, we\u2019re just now scratching the surface of what\u2019s possible. As AI develops, only more use cases will emerge, putting today\u2019s AI-powered retailers in an even better position to capitalize once they do.<\/p>\nGreg Jones is the CEO of tutch, an in-store digital platform that makes it more likely that shoppers will purchase\u2013and spend more.<\/em><\/p>\n<\/div>\n
Stores across the board are navigating staffing challenges \u2014 ranging from not having enough staff to not being able to keep the staff they do have fully educated on their large product offerings. These issues can directly translate into customers either leaving without finding what they need or simply buying what they came in for \u2014 and nothing else.<\/p>\n
Everyone in retail knows that upselling is the key to increasing order values. And customers are often willing to buy more than initially expected with just a little bit of prompting. However, human sales associates aren\u2019t perfect and get pulled into a million different directions during the course of a work day. Additionally, retailers have anywhere from hundreds to thousands of SKUs in stock and not even the most veteran store staff know every detail about each one. This makes it difficult for staff to make the best recommendations to the customers they do help.<\/p>\n
Digital platforms in the aisle can step in when these shortcomings are present, enabling shoppers to find products, get information they need, and discover products they might not have otherwise stumbled upon.<\/p>\n
Digital can even complement sales staff who are trained to navigate it, using it as a sales aid to answer complex questions and ultimately ensure the sale. AI can then step in to take that sale a step further by using what customers are currently doing and creating themed bundles based on data-driven insights. For example, a shopper in a hardware store is looking for a paint brush. AI imagines a larger painting project and automatically suggests painter’s tape, spackling paste, sand paper, paint thinner and protective sheets to cover the floor. It might even further show them a bundle of all of these items at a slightly reduced price.<\/p>\n
In this case, AI acts as an extra salesperson \u2014 one who never needs to take a break, never forgets to upsell, and will remember the customer every time they come in again \u2014 all with the purpose of increasing customers’ basket sizes, loyalty and value over time.<\/p>\n
3. Understand what inventory shoppers want in each location and how to merchandise it to increase sales. <\/strong><\/h3>\nUnlike their online counterparts, physical retailers have finite space to show all of the inventory they carry. This results in both direct costs and opportunity costs, such as the price of losing a customer when they can\u2019t find what they want or missing out on a chance to sell them more because they can\u2019t see everything that\u2019s available to them.<\/p>\n
Now there are multiple options to circumvent inventory restrictions in stores. Digital platforms, for instance, can help show the entirety of what a retailer has to offer, even when the products or sizes they want aren\u2019t available in-store. This alone can ensure that an engaged shopper doesn\u2019t leave the store without buying.<\/p>\n
As more shoppers use these platforms, they begin gathering information about what customers across the board are looking for in each store location and where there’s demand \u2014 or not \u2014 for different products. AI can then synthesize this data to optimize inventory management, predict what products and sizes should be featured in each store, and which would be best reserved for online or other sales channels. It can also tell retailers which products are the most popular and which are commonly considered or purchased together. All of this can inform exponentially more lucrative merchandising decisions.<\/p>\n
While retailers already have years or decades of sales data they could conceivably reference to understand these types of sales trends, it’s next to impossible to analyze these transactions manually, come up with actionable insights, and then turn those insights into a tangible merchandising plan. With AI, doing exactly this is table stakes.<\/p>\n
Looking Ahead<\/strong><\/h2>\nMany physical retailers have approached technology as a threat, but technology and brick-and-mortar aren\u2019t at odds. In fact, with the introduction of digital experiences, stores can offer everything that digital shopping channels do \u2014 with the added benefits that in-person experiences offer.<\/p>\n
Even retailers that have never considered doing anything<\/em> with digital can quickly get ahead of competitors \u2014 online and offline \u2014 by considering these practical ways of putting AI to work. After all, we\u2019re just now scratching the surface of what\u2019s possible. As AI develops, only more use cases will emerge, putting today\u2019s AI-powered retailers in an even better position to capitalize once they do.<\/p>\nGreg Jones is the CEO of tutch, an in-store digital platform that makes it more likely that shoppers will purchase\u2013and spend more.<\/em><\/p>\n<\/div>\n
Many physical retailers have approached technology as a threat, but technology and brick-and-mortar aren\u2019t at odds. In fact, with the introduction of digital experiences, stores can offer everything that digital shopping channels do \u2014 with the added benefits that in-person experiences offer.<\/p>\n
Even retailers that have never considered doing anything<\/em> with digital can quickly get ahead of competitors \u2014 online and offline \u2014 by considering these practical ways of putting AI to work. After all, we\u2019re just now scratching the surface of what\u2019s possible. As AI develops, only more use cases will emerge, putting today\u2019s AI-powered retailers in an even better position to capitalize once they do.<\/p>\n Greg Jones is the CEO of tutch, an in-store digital platform that makes it more likely that shoppers will purchase\u2013and spend more.<\/em><\/p>\n<\/div>\n