Is your company already using Artificial Intelligence? Some studies said that by this year around 85% of customer interactions would be managed by AI. We may not be there yet, but it is very clear that AI is giving companies a new competitive advantage.

Definitely in times where customer experience is the new imperative. Customers will get used to the total costumer experience, driven (and made possible) by AI. Not starting to experiment with AI, and not wanting to implement the tools that can help you manage all touchpoints with your clients, may become a negative impact for your businesses. Compare it with building a business plan on using the old yellow pages, without seeing the advantages of google and internet.

For the Belgian AI week (march 16 to march 20) we will post each day one big business and marketing evolution that will be driven by AI.


#1. More value and relevance: the total customer centric approach for AI in E-commerce

The new CMO should be a Customer Value Officer (read our blog about the new CMO). A Walker study reported customer experience will overtake price and product as the key brand differentiator. PwC found that for 65% of customers a positive experience will be more decisive for their opinion than their branding or advertising. For 86% it is even the key driver for their loyalty and decision to use the same company again or not.

Econsultancy recently asked what the most important characteristic is in order to establish a truly “digital-native” culture. For 58% of the participants it was to be customer-centric.

This customer-centric approach became way more complex in these digital times. E-commerce has revolutionized the way a consumer shops in our mobile world. Many ecommerces try to translate the best offline shopping experiences to the online world. For users it is the new way to discover products that may interest them.

But this new way of shopping causes new challenges: trough digital channels it is possible to establish a global reach, attracting millions of users (each using different devices) with different interests and different motivations. The user journeys become filled with too many touch points between companies and users. The amount of data generated by these new methods are simply impossible to grasp for a human mind.

Another problem for a lot of ecommerces is that users now often abandon the shopping process, because they can’t find the products that interest them. They leave the platform because the products or options showed to them are irrelevant.

But, that changes with AI: trough a policy of labeling gathered data and collected information, a decent analysis of customer behavior in each of the touch points can be conducted. And those insights can be used to improve the interactions and the customer experience. It will also ensure that the aha moments of the customer are more relevant and impactful.

Becoming more relevant to users starts with offering good recommendations. For ecommerces, with huge amounts of data to label and connect spread over different platforms and channels, online and offline, this can only be done by Artificial Intelligence. Trough AI, learning genuine consumer behavior and making predictions with large amount of data that is collected from user activities on different devices and pulling in 3rd party insights such as weather forecasts, becomes possible.

In the older AI models it was already possible to this for labels like ‘general’, ‘color’, ‘food’, ‘wedding’, ‘travel’,.. .  Newer models of Artificial Intelligence can also do this for visual searches or voice commands. And even the labeling of all the data, is no longer a human task. There is AI software that automatically tags videos and pictures.

This means that with Artificial Intelligence you can browse and search media assets using keyword tags or visual similarity. Or you can find matching products. AI is enabling shoppers to discover complementary products whether it is size, color, shape, fabric or even brand.

AI is also applicable to payment processing. Initially mainly used for fraud detection, AI is helping enhance customer service. For instance AI-enabled messaging chatbots help merchants in retail and hostel industries conduct payment transactions through a secure payment API. The AI bot is more personally  and provide more relevant recommendations. The conversion rates increases by 5 times than traditional mobile apps.

Using predictive Artificial Intelligence it will be possible to drastically improve recommendations for customers. Brands can scan trough massive amounts of data to predict customer behavior, and offer relevant recommendations to individual consumers. This level of intelligence is vital in delivering a personalized shopping experience for the consumer.


#2. Omnichannel hyperpersonalization & retargeting

Approx. 81% of customers have a desire for brands to understand them better (according to Accenture: ). This also means that brands need to know when to approach them and when to stay away.

This brings us to the concept of ‘Hyperpersonalization’.

“Hyperpersonalization takes personalized marketing a step further by leveraging artificial intelligence (AI) and real-time data to deliver more relevant content, product, and service information to each user.”

~ Todd Lebo (Convince and Convert).



Hyperpersonalization is not completely new. Personalized marketing is as old as marketing itself. Imagine the grocery store around the corner: why would you still shop there, while there is a huge and cheaper supermarket at the same distance? Because of the personalization. You know the owners. The owners know you. They just need a blink of an eye to understand your desires and preferences, and they will guide you trough the options without you even noticing it.

Hyperpersonalization does the same, but on a massive scale and trough online digital channels and ecommerces. Trough those channels brands will try to build the same kind of connection with their users, but virtually and with #SMarTech (Smart Sales and Marketing Technology). This can only happen with the help of AI and Machine Learning, since addressing each of your millions online followers in a personal way is an impossible task for a human team.

An AI tool can continuously monitor each of your channels, and each of the touchpoints between you and your users. Whether it’s a mobile application, website, email campaign or social media, google searches, AI can observe and interact 24/7, and thus create a total and universal customer view. Or simply said: trough AI it becomes possible to deliver an effortless and personal experience across all available platforms.


All of this is happening now, and in the future it will go even further. Imagine this combination of offline and online channels (however, we need to recognize there are some privacy issues to be solved in this thinking game).

A customer walks into a physical store in the retail industry. The shop has cameras to bust shoplifters. On these cameras it is possible to add a tool for facial recognition. True this software we can identify and record the dwell time of shoppers in the physical shop. Based on the amount of time the customer was overthinking shampoo choices, we can target that customer with shampoo ads on social platforms. So by the time the shoppers walks out of the physical store, he or she can get engaged in an online conversion funnel.

The example may be not very privacy proof, but it shows clearly how AI can help offline retailers building an omnichannel (retargeting) approach. Whenever it comes to discussing the topic of personalization, there is often a trade off with concerns to user privacy.  Brands are actively striving to take transparency, security and honesty to an entire new level. However, to achieve this, brands cannot afford to abandon user personalization, given its critical role in any successful e-commerce venture.

Collaboration Xs-silo is crucial. From IoT specialists, product development, legal, sales, marketing, business services. All of them at the service of your customer needs. And that is mainly possible if there is a clear customer vision with company wide metrics to be met.

#3. Marketing Automation

With AI we can finally start building experiences for the individual, and not the mass market. For each customer, there are a multitude of touch points  and influences that generate conversions. But for most brands it’s very hard to maintain this individual approach, since it is almost impossible to have a conversation with all of those users, to see which are the pain points.

With the use of AI driven marketing automation tools, such as chatbots or virtual assistants, the hyperpersonalization can be maintained in an automated way. This type of “conversional marketing” will create the personal interaction with users, even if it’s online and from the other side of the world. Because, with AI, it is perfectly possible to have a personal conversation with each of your potential users.

Customer service via social media is starting to establish itself as a requirement as opposed to an option. Chatbots can actively take on some of the important responsibilities that come with running an online business, particularly when it comes to executing tasks for operations and marketing. Chatbots can automate order processes and are an effective and low-cost way of providing customer service.

It means that these chatbots won’t only give you the competitive edge, it will also empower your employees. They will have time to do the real jobs, and leave the repetitive tasks to the AI tools.

Even the manner of conversating can be automated, with AI it will be possible to easily switch between vocal, written, visual and predictive approaches. Many AI systems enable natural language learning and voice input such as Siri or Alexa. This allows a CRM system to answer customer queries, solve their problems and even identify new opportunities for the sales team.

It’s also possible to integrate a chatbot system into a shopping cart. Once it’s installed, it can work with all the stores based on the platform. The more shopping carts that your chatbot application supports, the more potential users it has. It can also retrieve specific information such as product details, quantities and shipping details, and thus inform a potential user even better.

The online behavior of users is forcing retailers to change their price strategies. Therefore, it is imperative that multichannel retailers apply flexibility when it comes to the price structuring, in order to retain customers. This pushes more and more retailers towards “assortment intelligence”.

AI tools facilitate unprecedented levels of 24/7 visibility and valuable insights into competitors’ product assortments. Business can monitor their competitors’ product mix, which would be segmented by product and brand as well as the percentage of overlap. This allows businesses to quickly adjust their own product-mix and pricing with high accuracy.

If you want to tailor your problem-solving solutions and create a strong sales message that reaches consumers at the right time on the right platform, then integrating AI into your CRM is the way to go.


#4. Data analysis and predictive marketing

Ecommerce platforms are sitting on a goldmine of user data that could help their growth. But often overwhelmed, they are not doing anything with these data. With machine learning algorithms and AI these businesses could give themselves a full access to that gold mine. It would allow them to establish a predictive marketing strategy.

In a predictive marketing strategy statistical techniques for data analysis are used to predict the (online) behavior of users. With machine learning algorithms, data from previous users and visitors can be used to establish patterns and models. By learning how previous users did it, we can now learn how the next users will do it.

Around 90% of organizations using these predictive analytics have seen an increased return on their investment, according to Forbes. For 40% of those organizations that increase went up to over 10%, and sometimes even way more.

The numbers show that AI will become more and more important to stay competitive. Definitely since implementing AI does not need to change the structure of your company. Most companies already collected enough data to start applying AI. Just think about the information you have in your different channels, like the CRM systems, Google Analytics, social media accounts, … .

If we harvest each of those channels for information like website visits and behavior, loyalty program data, social media usage data, keyword data, conversion path, device, … it will be possible to create real-time insights into your audience. And thus will it be possible to know things like sentiments, cultural characteristics, social engagement and the way users search for information around a product or service your company offers.

And even better: AI will also give you insights on the best timing to reach out to certain prospects, when they are more likely to buy or not buy, and which arguments will be more or less decisive for making any kind of decision.

Merging the big data in your channels with AI will help you create the personalized marketing approach prospects are waiting for. It will allow you to hyperpersonalized and increase your relevance drastically. And most important: it will help you to install a total customer experience, from lead to loyalty.