![\"Retail](\"https:\/\/dmsretail.com\/RetailNews\/wp-content\/uploads\/2022\/05\/RETAIL-ONLINE-TRAINING-728-X-90.png\")
<\/a><\/p>\n<\/p>\n
The laziest way to attempt to sell something in a retail store is to let your associates ask “what” questions.<\/p>\n
What product do you need? What size? What color? What price range?<\/em><\/p>\n It’s what I call the “let’s cut to the chase” way of selling. Actually it’s what we call clerking<\/em>.<\/p>\n But customers don’t walk into your store because they need products. They walk in because they have problems to solve or outcomes to achieve.<\/p>\n They want a solution first, the actual product second.<\/p>\n This the Clerking versus Selling Questions<\/span>, part of the SalesRX framework for retail selling.<\/p>\n Not all “what” questions are created equal.<\/strong> The clerking questions (what size, what color, what price) are used to cut the sale down and tie both customer and salesperson to a specific product. They narrow your options fast.<\/p>\n The selling questions (what’s the occasion, what are you hoping this does for you) get to the why<\/em> that shopper is in your store today and what they’re hoping to solve. They open understanding.<\/p>\n Instead of asking product specification questions that narrow options, you ask selling questions that reveal the customer’s underlying problem or desired outcome. Some call this the shift from ‘what’ to ‘why’<\/strong> – from what size, what color, what price<\/em> to why are you shopping, why now, why does your current solution not work.\u00a0<\/em> The real story.<\/p>\n And the real story is where sales happen.<\/p>\n The difference determines whether you’re clerking<\/em> or selling<\/em>.<\/p>\n Here’s what happens in most stores:<\/p>\n Customer: “I need a new skirt.” Associate: “What size are you?”<\/p>\n Customer: “I need a desk chair.” Associate: “Chairs are over here.”<\/p>\n Customer: “I’m looking for running shoes.” Associate: “What’s your size?”<\/p>\n The associate heard a product request and started fulfilling an order. But they never discovered why<\/em> the customer is looking.<\/p>\n That’s the What vs Why<\/em> gap.<\/p>\n When you jump straight to product specs (size, color, price), you’re guessing at what the customer needs. You’re showing them a list of options and hoping one fits.<\/p>\n It’s easier, it seems, to find out right from the start if they have the money, if you carry the size, if it’s in stock.<\/p>\n That selling behavior comes from a long time ago when they taught salespeople to “tie down” a customer. Why waste your time on someone who doesn’t have the cash?<\/em><\/p>\n But that’s not selling. That’s order taking. And it costs you sales.<\/p>\n When you discover the why, you can recommend what actually solves the problem.<\/p>\n The customer who says “I need a skirt” might need it for:<\/p>\n Same product category. Four completely different outcomes.<\/p>\n Here’s what most associates miss: the customer is already matching what you show her against the why<\/em> she already has in her head.<\/p>\n She’s filtering every option you show through a question you never asked. If you don’t know she’s shopping for a job interview, you can’t help her see which skirt fits that situation.<\/p>\n You’re showing her products. She’s looking for a solution. And when nothing clicks, she leaves.<\/p>\n That’s not selling.<\/p>\n That’s hoping the product does the work for you.<\/p>\n And notice how much easier it is to build rapport if you know the context.<\/p>\n Job interview?<\/span><\/em> Now you can help her feel calm and sharp.<\/p>\n First date?<\/span><\/em> Now you can help her feel confident.<\/p>\n Lost weight?<\/span><\/em> Now you can congratulate her and celebrate the win.<\/p>\n Instead, most associates get stuck in features.<\/p>\n “It’s a poly-wool blend.” “It comes with a belt.” “It’s machine washable.”<\/p>\n Features matter, but not before you understand what outcome the shopper is trying to achieve.<\/p>\n You have to use open-ended questions to get at the real challenge, the stuff that reveals why<\/em> someone is shopping and what outcome they want.<\/p>\n Instead of a product spec question: “What size skirt do you need?” Ask the why question: “What’s the occasion?”<\/em><\/p>\n Instead of a product spec question: “What’s your budget for a chair?” Ask the why question: “Walk me through how you’ll use it.”<\/em><\/p>\n Instead of the product spec question: “What brand\u00a0of running shoe do you normally wear?” Ask the why question: “What do you wish your current ones did better?”<\/em><\/p>\n The second question gives you context. It tells you why<\/em> they’re looking so you are on the same search.<\/p>\n And that’s what allows you to recommend the right product at the right moment.<\/p>\n Knowing the why is only step one. What you do with that information is where the sale actually happens.<\/p>\n Let’s say your associate learns the customer needs a skirt for a job interview next week. She’s nervous. She wants to look put-together but not overdressed.<\/p>\n The associate response: “Here are our skirts. What size?” The professional response: “Let me pull together a few pieces that work for interviews. We’ll build you a look that says confident without trying too hard.”<\/p>\n That’s not upselling. That’s solving the problem.<\/p>\n So can AI do this?<\/p>\n Here’s what most retailers are missing about AI.<\/p>\n Most people think the future of shopping is a chatbot that answers “what” questions:<\/p>\n Do you have this in a medium? What colors does it come in? What’s your return policy?<\/em><\/p>\n That’s not the future. That’s a FAQ with a personality.<\/p>\n The real opportunity is contextual help:<\/p>\n “Show me outfits that would be good for a first date.” “I’m going to London this weekend, what works in that weather?” “Here’s a photo of my entertainment room, what fits this space?” “Help me pick the size I won’t return.”<\/p>\n That’s AI doing the why<\/em> work. It’s recommending\u00a0based on weather, matching products to photos, and predicting what size you’ll actually keep. And it can tell you why it picked something for you.<\/p>\n But even if AI recommends the perfect product, here’s the real question:<\/p>\n What are the odds it’s actually in the right color and size right when I’m willing to buy?<\/p>\n That’s one reason customers still go into stores. They don’t just want a recommendation, they want certainty.<\/p>\n And there’s another problem no one wants to talk about:<\/p>\n A lot of “AI personalized recommendations” are really paid placement disguised as helpful.<\/p>\n The retailer doesn’t just want to show you what’s best for you, they want to show you what’s in stock, what has the highest margin, or what a brand paid to push to the top.<\/p>\n They’ll call it personal. But it’s still merchandising.<\/p>\n That’s why a stylist from your local boutique can be more valuable than the smartest chatbot on the internet.<\/p>\n A good stylist isn’t trying to make you believe a product is perfect for you. They’re trying to help you get the right outcome, even if it means saying, “Not that one. Let’s try this and if that doesn’t work, we’ll keep on until we get just the right one you’re comfortable with.”<\/p>\n Trust beats tech. Every time.<\/p>\n The technology is ready. The behavior isn’t. So with ChatGPT, shoppers get the same limited results.\u00a0<\/p>\n But the in-store associate who listens and solves problems will still outperform both.<\/p>\n Customer walks into a furniture store. Associate: “What room gets the makeover today?”<\/p>\n Customer: “I need a new desk chair.”<\/p>\n If the associate starts collecting product specs<\/em>, it sounds like this:<\/p>\n Associate: “What’s your budget?” Customer: “I don’t want to spend more than $300.” Associate: “Let me show you what we have under $300.”<\/p>\n But asking selling questions<\/em>\u00a0sounds like this:<\/p>\n Associate: “Walk me through how you’ll use it. Home office, occasional use, what are we talking about?” Customer: “I work from home now. I’m in it probably 6 to 8 hours a day.”<\/p>\n Associate: “And what’s uncomfortable about what you have now?” Customer: “My lower back starts hurting after a couple hours. I can’t do a full day without taking breaks.”<\/p>\n Now you know why<\/em> they’re looking. They don’t just need “a chair under $300.” They need lower back support for 6 to 8 hour workdays.<\/p>\n And more importantly, a $300 chair probably can’t\u00a0fix that.<\/p>\n So your associate has to be comfortable enough to explain that in a way that’s helpful:<\/p>\n “I can show you what we have in that range, but if you’re in it all day and your back is hurting, I don’t want you buying something that doesn’t solve the problem. Let’s look at what actually works, and then you can decide what feels right.”<\/p>\n Without the why<\/em> behind the shopper’s visit, the customer looks at the $300 options and asks, “Is this all you have?”<\/p>\n The untrained associate says, “Yes, the other ones cost more.”<\/p>\n Customer walks out.<\/p>\n The manager asks what happened. Associate says, “They didn’t like what we had, they’re going to look around.”<\/p>\n Opportunity missed.<\/p>\n “What’s the occasion?”<\/strong> Use for gifts, clothing, events. Reveals context.<\/p>\n “Walk me through how you’ll use it.”<\/strong> Use for furniture, equipment, tools. Reveals function.<\/p>\n “What’s not working with what you have now?”<\/strong> Use for replacements and upgrades. Reveals the problem.<\/p>\n “What are you hoping this does for you?”<\/strong> Use when they’re vague or browsing. Reveals the outcome.<\/p>\n “What did you like about the last one, and what do you wish it did better?”<\/strong> Reveals what matters and what’s missing.<\/p>\n Once you know the why<\/em>, you have to frame the solution in terms that match it.<\/p>\n Most associates default to features. “This chair has lumbar support.” “This blouse is silk.” “These shoes have extra cushioning.”<\/p>\n Features describe the product. They don’t connect to the outcome.<\/p>\n Framing connects the product to what the customer actually wants;\u00a0features and benefits.<\/p>\n Feature:<\/strong> “This chair has lumbar support.” Framed benefit:<\/strong> “You said you’re hurting by 4pm. This is the chair that fixes that.”<\/p>\n Feature:<\/strong> “This blouse is machine-washable silk.” Framed benefit:<\/strong> “This works with three skirts we carry. You get a week of interview-ready outfits from one purchase.”<\/p>\n Feature:<\/strong> “These shoes have extra cushioning.” Framed benefit:<\/strong> “If you’re training for distance, these are the ones that won’t punish you at mile twenty.”<\/p>\n The principle is simple: use their words, not yours. If she said “job interview,” you say “interview-ready.” If he said “my back hurts after a few hours,” you say “the chair that fixes that.”<\/p>\n Don’t list the pieces. Name what it does for them.<\/p><\/div>\nWhy Most Retail Associates Ask the Wrong Questions<\/h2>\n
Why Context Matters More Than Product Specs<\/h2>\n
\n
How to Ask Why Questions in Retail<\/h2>\n
From Customer Discovery to Product Recommendation<\/h2>\n
How AI Changes Retail Sales (And What It Can’t Replace)<\/h2>\n
What Selling Questions Sound Like<\/h2>\n
Five Selling Questions Every Retail Associate Should Know<\/h2>\n
How to Frame the Recommendation<\/h2>\n