The following is a common scene of a non-alcoholic beverage salesperson: they approach a neighborhood store with a huge, cumbersome notebook where there are photos and details of all the products the company offers.
When they arrive, the storekeeper is very busy serving their customers who, in addition, due to health restrictions, are doing so from a prudent distance and with a grate in between.
Between one customer and the next, and with time against them – each daily route includes a number of stores to visit – they begin to offer the different product options in their different packaging and flavors: sugar-free, grapefruit flavor, orange flavor, in cans, in 750 ml bottles, disposable 1.5 liter, 2.5 liter, etc. Among them is the new coffee flavor, a product the company is looking to promote.
The salesperson juggles the notebook to show all the product options, until the storekeeper finally says: “Excuse me, I don’t have much time, I ask you for the usual, the classic. We’ll see new products another day.”
What this scene demonstrates is the great many obstacles that the sales force faces today when they have to go out and offer the product portfolio to the traditional channel. They must sell a large number of SKUs to a wide portfolio of clients, but they do not have the necessary tools to show the enormous variety of products that the company has.
New technologies provide a solution to these inconveniences and have recently become a very valuable tool for extending the product portfolio and decision-making.
The Traditional Product Portfolio: Short and Inefficient
In marketing, the portfolio is known as the entire range of products that a company has to offer to its entire audience, without distinctions. Within the portfolio there are groups and categories, according to the different variables established by the company itself.
The portfolio has certain basic features: breadth of product lines being marketed, depth of variants of each product, total extension of the company’s products, and consistency between each product line and its final marketing.
What is currently happening in the traditional channel is that the sales force does not have the ability to offer the product portfolio in a complete way. Out of 500 SKUs, for example, maybe they only have the time and space to offer 50 – and it’s still a lot – of which the storekeeper is left with only the 30 they already know. So there are another 470 products that could not be sold. It is likely that not all of those 470 products are intended for that type of store, but perhaps there are 150 or 200 that fit perfectly.
In this outdated model, the salesperson is merely an order taker. Many sales opportunities are lost; they cannot make recommendations or provide advice that will be beneficial to the company and the store.
How to Expand the Product Portfolio Through Technology?
Times are changing and the incorporation of new technological systems such as artificial intelligence and machine learning have the potential to improve the efficiency of mass sales strategies in the traditional channel.
Let’s start with a simple technology that many companies use today: a mobile app that allows visualizing the entire product portfolio with an easy interface and friendly design for anyone.
With that app, the sales force and the storekeeper can establish more fluid communication, see images, know details of all products and place orders online in just a few seconds, just by moving their fingers on a smartphone screen.
But technology can help even more. If that mobile app is added a data collection, cross-reference and analysis system, more efficient sales can be carried out. We are talking about an artificial intelligence system. The app not only displays the products and offers the possibility of placing orders online, but also begins to recognize sales patterns across all its users.
Personalized Sales Force recommendations
In this way, the sales force begins to have a precise tool to provide personalized advice. When the salesperson now communicates with the storekeeper, they will be able to guide them better: “Look, in addition to the flavors and packaging you always ask me for, I recommend you try these other flavors that the data indicates have actually sold very well in stores very similar to yours.”
The next step is the emergence of intelligent recommendations: by recognizing sales patterns and with the different variables of each customer, the system itself will be able to make automatic predictions and suggestions for the next orders.
That is to say, the intelligent recommendation will suggest, based on specific and precise data, which products are convenient to take, in what quantity and with what frequency. Also, being a machine learning technology, the more the system is used, the more accurate its result will be, since it is designed to “learn” from the experience of users.
New Times for the Sales Force
What has been shown is that technology is transforming the sales experience of the traditional channel. Those days of informality, estimated calculations and little product variety are becoming a thing of the past, opening a new path where salespeople have modern tools to extend the product portfolio and generate more sales.