Developing business intelligence tailored to Québec

We all have a folksy image of the village shoemaker who has known his customers for decades. How can we transpose this type of proximity that local merchants enjoy to a provincial scale? Let's take a closer look at the process Quebecor and Videotron have used to implement a data-driven approach with more than 2 million customers – a process that could be useful to integrate into your own business strategy.

All too often, local businesses that target Québec consumers fail to take advantage of a critical competitive advantage over foreign rivals: in-depth knowledge of their market from a data-based analytical perspective.

Take the example of the shoemaker or the local merchant: He is rooted in his community and his entourage appreciates him for this reason. As soon as he expands, that knowledge needs to be scaled up. The merchant must then adapt to the specific needs and characteristics of all the regions where he wants to do business. That's where things can go wrong.

A data-driven approach makes it possible to develop close relationships with customers across Québec. The latest iterations of this approach have seen the development of artificial intelligence (AI) and the thinking associated with which can also be used by many Québec companies. To develop AI that can support Québec organizations, a three-step approach must be applied in that sense.

1. Leverage Québec data

Too often in Québec, we tend to replicate the analytical recipes of our neighbours to the south. Of course, in many ways they are ahead of the digital game. Amazon and Google are prime examples. However, it is often forgotten that their algorithms were developed using massive databases (such as Axiom and Datalogix). In our market, the data is scant. Major American websites like Kraft recipes or Meredith magazines don’t have the same reach in Québec. Even when it comes to segmented retail, we tend to refer to static national Canadian platforms (by postal code) in which fewer than a dozen segments out of a hundred are relevant in Québec.

Data is like customers: it’s in constant motion. That applies to both fields of interest and destinations. If we want relevant market data to complement our own shopper insights, we have to go beyond the broad and often inaccurate audience descriptions offered by the major data resellers. We need data that describes Quebecers’ precise, dynamic behaviour, even if it is anonymized. Therefore, it is necessary to develop a digital product that can take a deep dive into Quebecers' interests and behaviours. This is why initiatives such as Quebecor ID enable you to improve the quality your customers' experience and increase their engagement.

2. Train the algorithms based on Québec’s characteristics

Here again, our reflex is often to transpose American ways of doing things to our market. Yes, we should definitely apply AI in order to model pricing, predict customer attrition and to better understand consumers' logical choices. But why don’t we bring the same energy to identifying and understanding the perceptions and emotions of today's consumers?
On this front, as in all matters relating to personal data, large companies and SMEs must first and foremost do their homework on ethical issues. How can we learn from processing the data and create value for our customers without infringing on their privacy? With sound data governance, it’s possible. Experience shows that a great deal of information can be extracted from completely anonymous customer databases, and today Québec’s business community does not have the luxury of foregoing this intelligence.

3. Use concrete methods in digital transformation and AI to propel your business forward

Machine learning works by testing different tactics. To achieve outstanding customer experience year after year, the omnichannel approach harvests continuous feedback from its customers.

How can the algorithms help us win the trust of our customers and surprise them – in a good way? In the thoroughly digital world of the future, businesses will have to learn how to generate positive emotions on the web by automated means. It's a big challenge. Nevertheless, hyperpersonalizing the customer relationship may one day help businesses increase their attractiveness on the web and ease potential frictions related to customer experience. In quantitative language, this can be expressed as maximizing your Net Promoter Score (NPS) and minimizing your Customer Effort Score (CES).

While this type of dizzying progress is being made in data management using smart algorithms, AI is attracting the business community and spurring the creation of super clusters. It isn’t always easy to bring the key players together around common goals in order to ensure the sustainability of Montréal’s ecosystem. But along with various local and international initiatives, this is an opportunity for many companies to strengthen their positioning here in Montréal, on the IA hub.  

The Strategic Forum on Artificial Intelligence organized by the Chamber of Commerce of Metropolitan Montréal is a good example. Participants at the Forum were not only able to step up the pace of AI integration within their own organizations but could also draw inspiration from the solutions and technological innovations of others to help them build promising AI that will open new doors in the future.

Capitalize on the digital revolution to support your business model

What then is the role of your AI-optimized data management tool? If this digital tool interacts with your data in addition to supporting Quebecers’ connected lives, it can be the privileged gateway to the development of proactive, cutting-edge algorithms. Quebec's business communities have everything to gain from exchanging and working together to find the right approach to exploiting data for the benefit of their customers. These economic players are not immune to the major international trends in customer service. They expect more relevance, customization and exclusivity.

To optimize its business practices here and abroad, opting for a smart digital transition requires working in synergy to find its “algorithmic-cultural” model.

About the author
Mario Lessard is Executive Director, Megadata Strategy and Business Intelligence atVideotron.

The opinions expressed in this post are those of the author and do not necessarily reflect those of the Chamber of Commerce of Metropolitan Montreal. As a result, the Chamber cannot be held responsible for published content.

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