Most e-commerce websites follow a similar guided selling pattern: A home page, category or landing pages (often referred to as PLPs), a search with faceted navigation on the search results, and product pages (often referred to as PDPs).
Users can choose to either browse through a category structure or input a search term and browse through those results; using the faceted navigation to filter those results further – along with a raft of other pages, of course.
Merchants are constantly trying to improve this process by adding features like predictive search or creating subject-specific categories such as ‘gifts’ or ‘holiday shoes,’ but this model still largely relies on the customer finding the products themselves via the search and filter tools available.
Considering this process in an omnichannel world, it’s akin to customers walking into a physical store and browsing the shelves before deciding what to buy. The physical store is likely to be laid out in categories (men, women, trousers, shirts, etc.) and the customer is free to browse the products themselves.
This model is perfectly successful in many industries such as fast fashion, supermarkets, etc., but is not very practical in others. Buying furniture, mattresses, computers, TVs, makeup, and a whole host of more complex and technical products often requires the support of an in-store assistant who will help the customer find the right product based on who it is for, how they want to use it, what their budget is, along with a whole host of other factors.
The staff in store are generally trained to enter into a conversation and ask a series of questions to help the customer narrow down their product selection, rather than just expecting the customer to find the right product themselves.
Take the example of buying a new mattress. You’d think that buying a new mattress would be quite straight forward, but it’s actually extremely complex. Do you need traditional springs, pocket springs, memory foam, or a mixture? What’s the difference between a mattress costing $250 and one costing $5,000? How firm should your mattress be?
If companies selling mattresses didn’t train their store staff to ask the right questions and provide them the knowledge to advise customers on the choice that’s relevant to them, they wouldn’t be very successful. As well as giving their store staff the required product knowledge, these retailers will also arm their store staff with a sales script, which is essentially an algorithm containing questions and answers. The staff adds a human touch to individual conversations, but they’re asking everyone the same questions.
Some bed retailers, like Dreams in the UK, have gone even further and invested in in-store tools that diagnose a customer’s size, weight, and sleeping position before asking a number of questions in order to give the best possible advice. This takes the in-store guided selling experience one step further in order to provide the customer with the best possible advice.
So, this begs the question: Why are so many retailers happy to provide such a consultative, conversational, and guided selling experience in-store, but then rely on customers to find the right products for themselves online? This is where online guided selling comes in.
The main aim of online guided selling is to replicate the in-store consultative experience in order to provide a targeted list of products to a customer based on their answers to a series of questions.
This may be as simple as asking a few questions about who will be using the products, what the budget is, and what color they want, but can also be a much more involved process with the questions asked being based on the answers to previous questions in a form of a decision tree. The goal of the string of questions asked is to mimic the conversational questions that an in-store assistant may ask the customer.
To complete in today’s omni-channel experience economy, businesses need to provide their customers with an online experience which is as good as, if not better than, they will get in-store. This is especially important when the products being purchased are technical or complex, or where the customer may not always know what they want.
These businesses have invested heavily in their in-store experience and the training of their staff to become product experts, as they know that this is what customers expect so why do many rely on customers working it out themselves online?
A number of companies, within specific industries, have implemented online guided selling tools to varying levels of success. They seem to be especially prevalent in the beauty sector where customers are used to consulting with experts in store. Customers may not know what products they should use for their specific skin or hair type and require the advice of a product expert to help with their buying decision.
A good example of this is Loreal’s Haircare Consultation Tool. This is an online tool that, through asking a series of questions, provides product recommendations to customers, in the same way that a Loreal hair care consultant may do in a department store:
Another example within the beauty sector is Pinrose’s scent personality quiz. This tool is a little quirky and asks the user to instinctively click on a series of images to determine the scents that best match their personality. I’d like to know what (if any) science is behind that. I tried it and it turns out that my scent personality is ‘girl next door’. Who knew?
Moving to the electronic goods industry, one in which I think guided selling is key, a good example is the KitchenAid product finder tool. This tool asks a series of questions about the customer’s personality, preferences and what they want to use the product for before providing product recommendations. This, again, closely mimics the questions that would be asked by in-store consultants in a physical store.
The next obvious evolution of guided selling involves chatbots and AI. Current guided selling tools are generally quite linear and are not very intelligent. Merchants will be creating a set of linked questions and answers and mapping of products or attributes to questions and answer chains. Some 3rd party guided selling tools such as Zoovu will have a level of machine learning to ensure that the most relevant results are provided to customers but the conversations that the tools have with customers are still quite linear.
Combining guided selling tools with chatbots would take them to the next level. Many sites now use live chat tools to connect customers with real people. These tools are often used for customer service queries such as ‘where is my order?’ but other companies use these tools to connect customers with product experts who can help the customers find the right products through a conversation, which will still involve the product expert asking a series of questions and providing a series of recommendations based on the answers given.
If a guided selling tool could be combined with a chatbot with a level of AI and natural language processing, it could engage in a conversation with a customer and automatically adapt the questions it asks the customer based on the language used in the conversation. These chatbots could be used across multiple channels, such as Facebook Messenger & WhatsApp not just on the e-commerce website. but also within in-store kiosks. A further step is to combine this with voice assistant tools such as Amazon Alexa or Google Home.
I think that we are a little way off from being able to easily do this but it seems obvious that this will come. Within some sectors, online purchasing will move primarily from a process of browsing a catalogue of products to having a conversation with a system which will give the customer a set of products that is personally curated for them.
I am surprised that online guided selling is not more prevalent than it currently is. For certain sectors, this could be a very valuable tool to help drive conversion rates and reduce returns as it results in the right products being put in front of the right customers. One likely reason for the limited usage could be the complexity of the development and implementation of such tools.
While a guided selling journey may seem quite simple, the complexity is in the creation of the administration tools that allow merchants to configure and build them. Rather than attempting to build their own tools, merchants should look at 3rd party solutions such as Zoovu or Conversity that offer sophisticated administration tools with simple integration into a website and other channels. Another important factor is how well it is executed. As with many online tools, if a half-hearted attempt is made to implement a guided selling tool with a poor user experience, it is unlikely to be successful. The experience should be slick and, crucially, the results should be relevant and valuable. If you can’t do it right, don’t do it at all.
For more articles by Branwell Moffat also see https://www.the-future-of-commerce.com/contributor/branwell-moffat.