Every advisory process has a vital point which is when a decision should be made. This is the moment when the Product Guide needs to find out which product type / or subcategory the user is most likely to buy. Finding out within the advisor process what product types the user is most likely to buy helps us to:
- determine which questions to ask in the future (dynamic question flow)
- know which (further personalized) content to display
- make sure we get the selection process as streamlined as possible
- avoid unnecessary steps and dead-ends in the selection process
However, most of the time you can not simply ask the user "hey, what do you need? A notebook or a tablet if you mainly browse the web and sometimes write an email?" since suggesting appropriate product types is the essential job of the Product Guide.
Examples: When Do You Need Smart Preselections?
Here are some examples where smart preselections make sense:
- Do I need a city or trekking bike? This can depend on comfort, where you use the bike, distance, equipment, weight - e.g. I prefer trekking bikes also in the city because they are lighter in weight and more versatile
- I want to learn piano - do I need an acoustic piano, an electric piano or a keyboard? Depending on where you live (apartment or house), at what time you play, what type of music you play (Classical/Jazz/Pop), if you want entertainment features or not etc etc .... Intelligent Guided Selling diverts the user away from receiving irrelevant suggestions or information, for example, tt makes no sense to get into the vast amount of possible electrical piano features if the user actually needs an acoustic piano.
"Smart Preselections are crucial to shorten the question flow and avoid bad recommendations - especially if the available choices are widely spread across categories. They help to determine what questions to ask next, what to avoid and which products to recommend."
How Smart Preselections Boost the Intelligence of Your Product Guide
The excentos solution: Firstly, let's assume you want to buy a pair of new jeans. Depending on your body shape, some jean cuts naturally fit better than others
The Jeans Product Guide asks the user for his size, body shape, style preferences - and then suggests the right jean type before continuing to the results list:
How Do Smart Preselections Work?
- all user input is taken into account to calculate a suitable product recommendation e.g. the jeans advisor asks about the user's body shape to find out which jeans cut is most likely to suit them best
- the recommendation is not a certain product, but rather a product type
- avoid wrong recommendations and reduce your return rates!
- make it transparent and demonstrate your expertise when consulting the user not just for which product to buy but also before explaining them the differences - this creates trust between you and the customer.
- give all freedom to the user! allow the user to change what you've suggested in case they want something different to your suggestion
What Smart Preselections Can and Can't Do
As far as we've experienced in hundreds of Guided Selling projects, Smart Preselections are really great in more complex buying decisions or in all assortments with totally different types of subcategories/solutions. When using Smart Preselections, it's important to make sure there is intelligent recommendation behavior - otherwise, they will lead the user to wrong product types and recommendations.
Don't try using preselections for replacing the final result list, or only letting the user select the product types. It's important to provide a good suggestion to the user to really guide them through the selection. If possible, provide reasons / arguments for the preselection to make them really smart.
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