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The first thing to know is the limits of AI, and after mastering the basic concepts, you will be able to build a large commercial software with artificial intelligence. This is a very powerful tool, but only if you know what to use it for and if you know how to use it well, it will give great results.
Always starting from a clear strategy of the business and the commercial force, AI builds good assistants, never a software will solve the problems of orientation or commercial strategy of a company.
As mentioned above, eommercial software based on artificial intelligence should be focused on creating good assistants, mainly for two types of users.
For them, artificial intelligence suggestions should serve to expand and improve the service they are providing to customers. Many times the salesperson works in a rather mechanical way, as a "simple order taker". A good intelligent assistant can take care of that mechanical, repetitive and more or less predictable part of the customer.
The IA will know the characteristics of each customer based on the learning obtained over time and sales history. This assistant will free the salesperson to do what the machine cannot, for example: sit down with the customer and get to know his needs and what he could do for him using his portfolio of products and services.
Artificial intelligence can be used to interact with the customer and get feedback directly from him. There is no need to implement a bot, it can be done by tracing how the customer navigates in the online store, if he accepts or not a suggestion obtained by the AI or if he is satisfied or not depending on some interaction with the customer service center, comments on social networks or by changes in his buying behavior.
Some concepts to be handled when implementing a commercial software to support sales and marketing departments:
Obviously, the first step to develop a client is to incorporate them into my client portfolio. When we want to develop marketing and acquisition campaigns, we spend a lot of effort in defining the "buyer persona", the "sales funnel", the sales and telesales team, etc. But we rarely think about using tools, for example, to sort potential customers or leads by probability of acquisition.
There are two reasons for this: on the one hand, there is a lack of knowledge of the tools and capabilities of artificial intelligence to do so, and on the other hand, it is not believed that there are enough variables of this "non-customer". The first is a knowledge problem, it can be solved, and the second is usually not true: if my business is B2B there is a lot of information available from companies that can be used for algorithms to learn and prioritize my potential customers.
And if the business is B2C, I can also know that potential customer, at least, their behavior (which is what interests the training algorithms): it is enough to use my digital channels: corporate website, online store and social networks (RRSS) and logically trace these channels.
This is the first thing to estimate about a current customer that we want to develop commercially: what is its potential or future value. It can have a positive potential: you can do more business, or a negative one: you can abandon my products and services.
Many times commercial strategies are proposed based on the potential of a customer. Surely many commercial managers have seen those brainy quadrants that more or less say: a customer with high value and high potential must be developed, with high value and low potential must be defended, and so on, until they reach customers with low value and low potential that it is better not to bother or invest anything in them.
But what very few commercial managers have seen is how a customer's potential is calculated or estimated. Important: of a customer, not of a segment, more or less specific market, but of a specific customer and for each and every customer.
It can be concluded that the first result that any AI-based system for business development should obtain is the potential of each customer. We must invest in those who have the greatest potential and who can have the most value for my business.
Once we estimate or predict what future value a customer can generate, the next step is to see how we can develop or defend those customers that have strong potential.
One of the most obvious ways to develop a customer's potential is for that customer to acquire new products and services. This is a range expansion: a new reference that is incorporated to the assortment of products and services that the customer buys from my portfolio, and in the case of high rotation goods, we intend that this incorporation is permanent, increasing the recurrent of that customer. A range expansion opportunity is that product or service that AI estimates has a high probability of being purchased or subscribed by the customer to develop the potential.
It is the business actions suggested by artificial intelligence that are easiest to measure, but this will be discussed in more detail when we talk about metrics or KPIs to measure the impact on the overall business.
In this case it is a product or service that the customer already buys but can buy in greater quantity or for a higher value (for example, because he/she purchases a premium version of a service). These are the opportunities detected by the AI that may require greater complexity to materialize, because they are products that are already being purchased and what is detected is that the customer buys them less than he should.
How is this development opportunity verified or materialized? There will be no choice but to use promotions or campaigns, which are explained in the next point.
Do you want to learn concepts and definitions about Artificial Intelligence and Machine Learning? Access our glossary
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