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Differentiating Your Company through the User Experience

How to integrate Content, Product Data and Knowledge to Meet Your Customer’s Needs

Organizations are continuing the never-ending journey of managing and applying information to solve problems and serve their customers by improving the e-commerce customer experience. The ability to do this well is becoming the core differentiator in the digital experience.  That experience is based entirely on information that the customer receives. The more effectively an organization can streamline the experience, the greater the competitive advantage.  Price may be a key consideration for some products in particular industries or potential customers; however, ease of doing business and ease of finding the answer can make price less critical.  This is why usability and findability are so crucial to the online experience. 

Usability and findability

But what is usability?  What do we mean by findability?  The answers may seem obvious at first glance, but what is usable to one person might be incomprehensibly complex to another.  People differ in how they think about the problem they are trying to solve (which is influenced by their background and level of expertise), and they may use very different terminology to describe their needs.   Their mental models – which reflect a number of factors, including learning and thinking styles – are different.  Everyone has a different frame of reference and point of view. Even when their needs are the same, the way in which users find the things that meet those needs can be very different. This is why usability testing should include users representing different demographics and customer journeys.  An approach that tests well on one group may test poorly on another.

The user experience is about much more than navigation.  Search results need to make sense by also reflecting the mental model of users.  That includes using facet labels with terminology that they understand, attributes for filtering based on the features that are important to them, and product details that are useful in making their selection.  Details that are captured and surfaced for actions such as comparisons need to be appropriate to the user, the product class and brand, and the problems being solved. This process may appear to be straightforward for some classes of retail and consumer goods; however, it is never trivial since the decision factors that are important to one person may be meaningless to another.  In B2B contexts when products are technically complex, surfacing the right information becomes extremely challenging.

Search, navigation, and weak signals

But there’s even more to designing a great customer experience, because navigation and search are only two of the signals that users can present that provide clues about their intent.  Search and navigation are weak signals.  Search terms can be very ambiguous.  They are typically short, andare only an approximation of a user’s intent or need. Faceted search is often incorporated to help disambiguate the user’s short query.  A search for “shirts” on Target.com will return several facet categories to refine the ambiguous query.  Search becomes a conversation.  When a potential customer says “I need a shirt,” the system responds with “what kind of a shirt do you want? T-shirt, polo shirt, button-down shirt…” etc.

The well-designed e-commerce platform should interpret the query and present appropriate results. If the user is authenticated, the results from the weak signal (a short search query) can be informed by purchase history.  If I buy dress shirts of a particular brand and style, the system can exclude Harry Potter, Metallica, and Superman T-shirts (the choices presented to me when I searched a site recently) and give priority to my brand of dress shirt. While the majority of searchers using that keyword may be buyers of logoed T-shirts, the additional signal of my past purchase would override that result. Brand loyalty is an integral key to personalization, and an important consideration in customer retention. 

For most retail e-commerce sites, various approaches for providing suggestions use prior purchase histories and shopping basket analysis (“people who bought this, also bought the following”) as well as explicitly stated preferences.  These approaches are far from perfect but can provide some uplift.  More sophisticated strategies will be based on a detailed understanding of customer needs and will drive dynamic content based on those needs to create customer loyalty.  

WATCH: 4 Digital Experience Tools That Drive Real Results

Salesperson as a recommendation engine 

Let’s the idea of how to assess and respond to customer needs from another perspective. [Not sure which concept was being referred to. Change if the suggestion does not match the intent.]  If I walk into my favorite men’s store, the salesperson does not need to ask what kind of shirt I want.  He knows my style from working with me in the past, and typically shows me interesting new styles and matching ties, etc. It is unlikely that he will bring something that I don’t like. I appreciate his knowledge; it saves me time and effort.  The goal of an online user experience should be to capture the same understanding of customer needs that a knowledgeable salesperson would have and offer the products that a good salesperson would have offered.  The salesperson is a recommendation engine that uses past purchases and user preferences to make those recommendations. This is personalization at its core.

In technical sectors, the salesperson might be a solution engineer whose knowledge and expertise becomes highly valued and even indispensable to the customer.  They not only make product recommendations but help to guide customers in defining and solving their problems.  The best salespeople work with the customer’s interests at heart to achieve the best outcome, even when it does not further their sale.

This is the value-add that many organizations strive to provide, especially when some of their products in isolation are considered commodities.  A generic sensor component can be procured from many suppliers.  However, when a specific component is an integral part of a solution design, it is no longer a commodity.  Many industrial suppliers have built their reputations on becoming an extension of their customer’s engineering team and by providing reference and specification materials in the form of industry standard catalogues. 

Automating expertise: e-commerce site as a virtual salesperson

For B2B sites that provide solutions to meet the needs of customers using live chat from skilled experts, the need for knowledge-driven automation approaches is crystal clear.  There is no way to scale complex purchases with manual processes – especially when the salesperson requires years of expertise to be fully productive.  Knowledge-driven presales and support will not be possible at scale without embracing a holistic approach to product data, content, customer data and knowledge to incorporate all these into the online experience. 

The need for knowledge-centric e-commerce will increase, especially for industrial suppliers, as human expertise becomes scarcer as senior level people with years of accumulated knowledge retire.  In some situations, configuration tools and applications can fill some of the gap.  Configure Price Quote (CPQ) tools contain embedded knowledge about how systems are created using components.  These applications are at the intersection of knowledge, content, and product information. 

Call centers that support sales using highly skilled experts can save a tremendous amount of time by providing product selection and configuration tools.  Salespeople at one industrial supplier spend 70% of their time helping customers find and select products.  The company expects to cut that time in half by deploying new technologies that will allow customers to select typical configurations, freeing the sales staff to prospect, help customers with complex needs, and engage in other higher value activities. 

Chatbots are also being developed to assist in offloading simple interactions; however, those interactions will be increasingly become complex knowledge-focused interactions – from product configuration to complex troubleshooting and advisory work.  The ability of a chatbot to function is dependent on a foundation of knowledge and a comprehensive knowledge architecture.  That architecture will encompass structured and unstructured data providing common organizing principles across systems and applications. This means that an enterprise architecture will be needed to provide high levels of sophisticated functionality. 

Knowledge = applied content

Well-structured and well-organized content is the explicit embodiment of knowledge; in fact, one could say that knowledge is applied content.  The challenge lies in extracting knowledge from the expert who has the answer, structuring it in such a way that it can be accessed, and identifying the signals from the user that allows the information to be surfaced when it is needed to meet customer expectations. 

Clearly, knowledge as reflected in content is critical to the success of a site.  It’s not just support content or reference content – it’s the content that helps the user throughout their journey from awareness and initial investigation through selection, purchase, acquisition, usage, and ongoing support.  Upstream knowledge processes and sources (typically within engineering groups) also have to be managed and well curated – captured and structured – to prevent the need for acts of heroics downstream once products are launched and customers have questions and problems to solve. Without a solid information architecture that allows for effective content management throughout the information lifecycle, neither customers nor employees will be able to access the content they need.

READ: Tackling Complex Product Configuration Documentation Challenges with Component Content

Being intentional about product data, associated content, and knowledge assets is increasingly part of e-commerce programs.  Many organizations are still struggling to get their product data in shape, but with new marketing tools and technologies, they have started to better manage content and rich media in support of the customer.  A knowledge-centric approach goes beyond marketing content and product-related rich media, and extends the experience to provide more complex approaches and solutions to customer challenges. 

Knowledge supports the journey

At every point in the customer journey, customers need information and content tied together by the organization’s knowledge. This knowledge is in the form of product details, (including features, pricing, and specifications), instructions on how to solve problems, bundles of products that comprise a solution, maintenance details, reviews, warranties, photos and diagrams, engineering drawings and so on.  The ability to assemble real-time data dynamically in response to changing customer needs and context is required in order to provide an advanced, personalized website or an omnichannel experience.  An intentional approach to knowledge and a well-designed architecture are the ingredients that tie all of the pieces together. 

For a look into how we use information architecture as the foundation for digital transformation read our whitepaper: Knowledge is Power: Context-Driven Digital Transformation

 

Seth Earley
Seth Earley
Seth Earley is the Founder & CEO of Earley Information Science and the author of the award winning book The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster, and More Profitable. An expert with 20+ years experience in Knowledge Strategy, Data and Information Architecture, Search-based Applications and Information Findability solutions. He has worked with a diverse roster of Fortune 1000 companies helping them to achieve higher levels of operating performance.

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