Content Intelligence Network
Perhaps you have been able to watch (and I hope, not “live”!) the movement of a snake. Given that they use both physical and digital channels at the same time, a similar non-linear path is experienced by today’s consumers. However, a number of companies, still anchored to obsolete business models, do not know how to offer these customers, who are quick as snakes, effective and engaging journeys.
The best way to optimize the customer experience is to make it data driven. However, the majority of customer data available is hidden beneath the surface and only the “tip” of the iceberg is visible. Given the complexity of this material, there is Artificial Intelligence to unravel the “tangled mass”. It can extract insights to be taken advantage of to deliver better customer experiences.
We are facing a breakthrough: AI will influence every aspect of interaction with consumers. When we speak about AI, we are referring in particular to one of its subsets: Machine Learning (ML), which is at the base of the system through which computers process information.
The AI algorithms analyze and process the data. They recognize their characteristics and “learn” from their examination, extracting value. And, the higher the quality of the data inputs that are “fed” into the machine, the better the predictions will be that we will go on to create.
Going into more detail, the future is in the hands of Deep Learning (DL), which is a form of ML designed to replicate the principles with which human brain neurons work. This is scalable and, once it has been trained with a large amount of data, it can bring to life well-defined strategies that can be used by the machine without human intervention.
As Forbes writes, the results can be seen immediately: 75% of companies that use Machine Learning increase their customer satisfaction by more than 10%. But, we need to fully understand what the marketing environments are in which this Valhalla of technology can be taken advantage of fully.
Why is AI important for Marketers?
On Medium, Steven Harries identifies three macro-sectors in which AI can be applied to marketing with large business advantages:
1) Consumer engagement
- Insights on customers based on AI, targeting and personalization
Thanks to machine learning, it is possible to give rise to customer segmentation models that extract dynamic and homogeneous groups based on behavior and preferences on a “micro” level.
Indeed, before AI, it was difficult to find new potential customers beyond the “classic” segmentation target. Instead, now, each potential customer, even anonymous ones, are “monitored” by AI, which registers every action carried out. From the analysis of their behavior, it discovers the search intent, or rather, the need to be satisfied, which sometimes has not yet been expressed or requested.
Let’s not forget that, thanks to features such as image recognition or speech to text, we can now obtain data even from multimedia media, such as images and videos.
By applying predictive algorithms, which identify the probabilities of future results based on “historic” data, to behavioral results, those personality traits that are linked to specific triggers and behaviors are identified. The unstructured data therefore become structured. In this way, AI is able to recognize the various engagement models and the “teasers” to untangle the knots of millions of user actions and interactions with a personalized response. Indeed, this takes into account the various contextual factors and, therefore, manages to present the message to the customer at the precise time it is needed, exponentially increasing the conversion possibility.
When it goes to “discover” models in the data generated by customer browsing, AI manages to predict other aspects too, such as customer abandonment rates (churn) or customer lifetime value. This allows marketing operators to commit to a real proactive prevention.
- Creativity and design
AI algorithms create specifications for every customer, analyzing billions of data points. They help to understand which messages, and creative and psychological elements encourage the objective more. These new datasets reveal which esthetic and design elements should be used to meet the customer halfway and provide them with the best browsing experience.
2) Brand consistency
With AI it becomes easier to ensure brand consistency as the classification of contacts and content can be improved, training AI engines to tag in an increasingly precise way based on an official brand taxonomy, which also includes products.
3) Corporate strategy
Companies, freed from the highly repetitive activities that occupied employees previously, as well as gaining in productivity and time saved, can completely dedicate themselves to innovation and creativity. They can discover how they can improve and guide user experiences so as to achieve the final conversion result in a more effective way.
Furthermore, the AI algorithms help to find new business opportunities:
1) identifying consumer obstacles, determining where their needs are not being fulfilled
2) discovering new opportunities, identifying which emotional and functional areas would be most appreciated by consumers, and investing in these
3) widening the industries that the brand can extend to, identifying new potential customers from their behavior