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These days, customers are flooded with masses of product information and promotions. In most purchase decisions, the choice is so overwhelming that they don't even know what to buy anymore.

To prevent customers from leaving your website dissatisfied, intelligent recommendation behavior helps you to create a personalized and user-friendly shopping experience. Displaying the right products or services to the right customers is not only key in terms of providing truly relevant content but is also the key to success in winning and retaining customers while also successfully engaging with them.

We are all familiar with the more conventional ways of trying to guide our customers through our e-commerce website. For example, 90% of all online shops have a faceted search engine or standard menu and category navigation bar. It's something a customer simply expects to see — but as e-commerce develops and retailers sell more online, customers require more advice and guidance.

Artificial intelligence is transforming retail to make online shopping more efficient and personalized with the help of predictive analytic tools and Guided Selling systems such as Product Guides and Digital Advisors.

In this blog post, we will go into:

• Why conventional search systems such as faceted search engines don't quite make the cut in the advancing world of e-commerce
• How you can discover whether your website or shop has suitable mechanisms in place to provide customers with good recommendations
• The steps you can take to improve your shop's user experience and navigation
• The latest kinds of recommender systems available to you on the market right now

Source: Sony

Unenticing and filled with technical detail which not every customer will be familiar with, this faceted search provides no assistance to customers who are unsure of what they need or want.

The faceted search is also a distant resemblance from how humans would naturally interact and converse since it is unable to advise customers on what product to buy.

Source: Sony

Naturally, a must-have on any website, the menu/category navigation helps to filter out different kinds of products but is unable to advise any further. Once the user has said which kind of product they are looking for, they reach a dead-end.

It all starts with understanding your customers and being able to map out the customer journey from their perspective. This way you can fulfill the requirements of every individual customer and provide them with intelligent product recommendations which are relevant to them.

Technically, it is complex to achieve good recommendation behavior but if you take it down a level, you can think about it in a less-abstract manner. Imagine your most charming sales rep. from one of your stores. They know exactly how to transform any customer's requirements into valuable recommendations that the customer will most likely buy.

Good recommendation behavior means that products or solutions are displayed in a results list, presenting the most suitable products first. The products you recommend should not only suit the customer's individual needs but also support your company's sales and marketing strategy.

An overview and analysis of different kinds of product search and recommender systems and what they achieve.

Human Factor

Analytics

Conversion

Knowledge

Source: VAUDE Tent Adviser

✓ Users don't need to search far and wide to find the most suitable products

✓ Users with no prior knowledge about what they are looking for can be easily guided and advised

✓ Users are presented with product explanations which inform them which products would suit their needs best and why

✓ Users are provided with a comprised list which is personalized and only shows the most relevant recommendations

Source: North Face

✗ All products are mixed together so the user has to figure out which would suit their needs best

✗ Filters such as weight (lbs) and floor area (sq ft) are too specific and many users would not know what size or weight they require

✗ The order of the results list is not personalized to the individual user's needs

1. Brainstorm

• Put yourself in the mind of your customer
• Map out their shopping journey from when they enter your online shop until they reach the checkout
• What information do they require when considering a purchase?
• Consider the complexity of your product. If your products are more personal and less dependent on the specifics, you will require questions which focus more on personality traits and behavioral tendencies. It could be anything from fashion products, perfume, books, home and lifestyle products, toys — or maybe even holidays.

A tree diagram which maps out part of a customer's journey and possible thought process when buying a camera.

2. Apply

• Apply this knowledge to create a question flow and product recommendations for your Product Guide
• Include relevant attributes, such as personal requirements, which device type is appropriate to the user, sizing, price ranges, preferred brands etc.
• Find a software company who can build your Product Guide. They will need to combine your consumer knowledge with your product data, in order to make a well-functioning guide which you can easily integrate into your website.

A completed Product Guide designed to advise people when buying a new camera

3. Track

• Optimize your Product Guide with analytics tools and track your success
• Find out which products people buy most with the Product Guide
• Where do people click and where do they drop off?

Example of data sample taken from one day period of the Product Guide after going live. It shows intense usage with 16 actions per visit and a long visit duration with over 5 minutes

Consumer insights extracted from Product Guides help companies with future targeting since the recommendations provide useful information, such as: purchase and returns history, preferred brands, size and measurements, preferred colors etc. This allows you to offer more personalization through cross-selling recommendations, more insightful email marketing campaigns and landing pages which provide relevant recommendations.

Source: Asos

Personalized recommendations and styling advice calculated from the user's buying/browser history are great upselling features and allow you to showcase more products which your customer is bound to love.

Source: Easyjet

Email marketing based on a customer's purchase history, browser history or user segment data is the ideal way to tempt customers back into your shop.

Landing Page Recommendations

Source: Samsung

Welcome new customers onto your website. Creating landing pages for popular products allows you to attract new customers and increase traffic to your shop.

Out with the old and in with the new; start building a modern recommender system today

Find out which suits your company's needs best

As fall approaches, homeware and furniture brands are highlighting their best Scandi hygge, nomadic prints and grey hues. As ever, the season trends have been unveiled on thousands of furniture and homeware sites; ready to be snapped up by eager home-lovers and design enthusiasts.

As with many other consumer products, technology continues to play a major role in helping consumers make a choice in the home and furniture retail space.

A lucrative and ever-growing market, fashion retailers are also starting to realize the potential. Urban Outfitters, Asos, Zara and H&M are just a few of many who are now selling furniture, textiles, ceramics and home accessories online. With this increased competition, traditional furniture and homeware brands have been put to the test.

We take a look at how some brands are performing well to triumph over the likes of fashion retailers, by providing a personalized service which online consumers love.

MADE and Dulux take personalized advice online and assist their online shoppers to find their perfect products.

With just a few simple questions, the user provides valuable information about their personal taste and preferences. The product advisor then finds recommendations which are personalized to suit the user's needs. Product advisors can also be great fun for your users to interact with, as they add that special touch to the online shopping experience.

Without product advisors, users can become easily confused amongst the thousands of products a website has to offer. By minimizing the amount that users see and focusing in on what matters to their individual needs, companies increase their chances of getting a sale.

MADE Sofas, Furniture & Homeware — https://www.made.com/

Source: MADE

What we love:

• ✓ users are provided with an array of images which portray different styles and inspiration.

• ✓ the social media-style interface is interactive and allows users to easily scroll and give an image the thumbs up.

• ✓ by providing visuals instead of words, it also makes it quicker for the user to envision their ideal home.

What we love:

• ✓ the feature to email ourselves or social share our results with friends.

• ✓ personalized color, material and print recommendations

What we love:

• ✓ personalized product recommendations which suit the user's taste.

• ✓ products shown within different settings to further help the user imagine their perfect home.

What we love:

• ✓ Dulux place their Product Guide as the very first thing a user sees when entering their website.

• ✓ the Product Guide caters to all types of customers: those who already know what they want and those who require assistance.

What we love:

• ✓ visually appealing

• ✓ users can state the finer details such as location, surface and finish.

What we love:

• ✓ practical tips such as primary color options, as well as colors to be mixed

• ✓ only shown the color which we stated we were interested in

Image searches help users to find products via images instead of text. They work by using query by image content (QBIC) and content-based visual information retrieval (CBVIR). Users simply upload an image they like or feel inspired by and the website search engine delivers similar products available within their product assortment. In addition, if users don't know the name of a product but simply have an image — it's a perfect way for them to identify a product name and get more information.

• ✓ image attributes instead of descriptive metadata to search — helpful if the user doesn't know the product name or wants to find visually similar looking products

• ✓ user-friendly interface and easy for mobile users who can upload images from their phone galleries

Live chat functions and virtual assistants mean that you can provide your users instant feedback and support and at no extra cost for them.

"38% of consumers are more likely to buy from a company if they offer live chat support." — kayako

In comparison with traditional phone support and customer hotlines, live chat and virtual assistants are much more convenient for the majority of customers.

Live chat can provide answers quickly and has the ability to mimic natural style conversations which you would have in-store with a human sales-assistant.

Virtual assistants are the automated version of live chat tools. No man-power required: just AI and machine learning, a virtual assistant can advise users within seconds and quickly point them to the products they are looking for.

• ✓ by showing the face behind the chat operators, it makes the tool much more approachable and personal.

• ✓ the integrated search engine is a more engaging way to provide answers to FAQs

• ✓ users get an answer within a few clicks.

• ✓ users have a live chat option, should the virtual assistant not give them sufficient enough advice.

Wondering why your customers are leaving your website early or simply don't make it to the cart? It could be down to the lack of personalization on your website.

Personalization tools such as Product Guides, sophisticated search engines and virtual assistants can help your customers, your customer support team and best of all, your revenue!

Relevant and personalized information is the key to effective inbound marketing activities. Known as attention economics, there is only so much information a human can process and will choose to pay attention to. Therefore, it's important that what you provide stands out, but is also relevant to your different segments and target groups.

"Attention is a resource, a person only has so much of it" - Matthew Crawford on attention economics.

Your different consumer segments require different levels of information and of different depth and complexity. For example, you receive 100 site visitors from an ad campaign, which you ran. Only 5% of these automatically convert and make a purchase. The remaining 95% need 'warming up' before they get to the cart. Sending them inbound marketing material over a defined period of time will help to educate and subtly persuade the lead, as to why they need your product.

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