Increase Sales by Narrowing Customer Choices

Photo: diego_cervo

In an ever-growing field of choices courtesy of the long tail of inventory and loads of information, how does the customer choose? Or, rather, how do you help the customer narrow down choices and make a decision?

During a recent shopping excursion at a brick-and-mortar location, I noticed that a specialty retailer adopted what I considered an online model of filtering and refining choices for its customers.

The selling technique looks something like this:

  • Here’s what we have
  • Here’s where you can find ______ (fill-in-the-blank product category)
  • Here’s what is on sale
  • Here’s what is popular
  • Keep looking and you’ll find what you want (or leave without buying)

Such tactics are easy to implement but not helpful for time-pressed and information-overwhelmed customers. Fortunately, many traditional and online businesses offer vastly better ways of guiding customers through the purchase decision-making process.

Allow Customers to Specify Product Attributes

Product-selection navigation tools allow online shoppers to filter choices based on a hierarchy of attributes, so that the list of suitable items progressively narrows to a manageable number. Very often, this technique works beautifully. The customer finds a handful of items that fit her criteria; from this list, she makes a purchase decision.

Many times, though, the buyer discovers that there is not an exact match between her requirements and the product offerings. Progressive refinement yields zero results rather than the optimal solution. So, she must reconsider. Her next steps are to prioritize requirements, predict which attributes can be found in a single product, and keep searching or, eventually, stop trying.

An even better way to narrow choices is to allow the customer to specify multiple desired attributes simultaneously and continuously select and deselect criteria without having to restart the narrowing-of-choices process over and over again. In a recent visit to, I discovered NavWow, a filtering method that offers a more fluid selection process, rather than a linear drill-down approach that guides customers through the navigation of choices.

The online seller has also expanded its list of attributes from standard criteria such as size and price to characteristics such as “Performance” and “Personality.” (Note that NavWow is still under development and available only to randomly selected customers).

Be Flexible with Recommendations

The formulaic approach of matching customer requirements with appropriate products is useful but limited in its effectiveness for customers who have difficulty defining and articulating needs.

For example, not too long ago, my husband and I were shopping for a new washing machine. We were debating the relative merits of high-efficiency performance, front-loading design, and large-size capacity. As we wandered the aisles of the big-box store, sorting through our options, we overheard a sales associate mention a key benefit of the larger machines: these models could readily handle oversized bedspreads (a situation I had struggled with in the past). This nugget of information – absent from the retailer’s website and excluded from the comprehensive list of benefits associated with product features – helped us make our decision.

So, first recognize that customers need your expertise. Then, be flexible as customers share priorities and then reprioritize their requirements based on your insights.

You can guide the filtering and refining of choices using these methods:

  • Clarify what anticipated end-uses are reasonable and which are not;
  • Explain which attributes are critical and which are convenience- and fashion-oriented;
  • Present features that boost performance;
  • Gently correct false assumptions customers may have about the value of certain attributes or the likelihood of certain occurrences that may impact their decisions;
  • Share real-world experiences on practical applications.
  • Use Customer Information to Guide the Narrowing Process

Online businesses in particular make recommendations based on several things, including:

  • customer profiles;
  • past purchases;
  • purchases of those who bought similar items to the ones viewed or purchased;
  • decisions made by those in similar demographic pools.

These techniques can yield spot-on suggestions or irrelevant results. Netflix’s system of recommending titles based on viewing history and customer ratings can be insightful.

But things can go wrong. To give me ideas on titles to consider on a Saturday night, for example, Netflix revealed that those in my city were viewing an X-rated movie. While interesting, this information did not help me find a suitable movie for my family.

Carry the Right Inventory

The benefit of long tail inventory (that is, deep and broad product offerings for niche markets) is the availability of items to suit the needs and preferences of an increasingly diverse base of customers. The downside is the difficulty in discovering the perfectly-matched product in a vast sea of inventory.

To offer the right choices to customers, do the following:

  • Decide what market segments your business serves and define each type of customer among these segments;
  • Figure out what these customers expect in terms of product design, performance, features, fashion, and cost;
  • Know the preferred use case of your product lines;
  • Learn what influences the purchase decisions of your customers (which may be based on product reviews, recommendations from social and professional networks, desire to have newest innovations, etc.);
  • Stay on top of industry trends, new product offerings, value-added features, etc.
  • Merchandise your product line to resonate with your customer. That is, filter and refine choices for customers before they visit your website or brick-and-mortar store.

Offering everything can mean that your customer may never decide. Let your expertise refine choices for your customers. After all, they’re coming to you for information about what to purchase, too.

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