In 2019, on our blog, we’ll be hearing from digital agencies who work in close collaboration with brands to help them make the most of their data. Today we’re sitting down with Didier Richaudeau, partner in charge of data activities at Equancy. His areas of activity stretch from data science and marketing performance measurement (including digital and media analytics) to technology advising and implementing big data platforms. His teams work closely with clients like Nissan Europe, DisneyLand Paris, Volkswagen, Picard, Sephora, Bayer, and Pierre & Vacances Center Parcs to help them design their data strategies and implement them operationally. Let’s get straight into his interview!
What major data & analytics challenges are you currently seeing?
The main challenge is being able to deal with data silos. And notably to open analytics data up to other departments (other than web) within the company, because this data has true value that can be leveraged by other teams. Putting this data in the hands of merchandising or pricing teams, or those responsible for sales provisions, represents true potential for knowledge and operational efficiency. That said, we must also be conscious of reality. Today, data is power. Within a company, each department tends to save its data in its own little territory rather than sharing it. There’s therefore a major challenge around governance. The technological challenge is also immense: in other words, finding solutions capable of handling this variety of data. For example, the product department might not naturally have the right tools (and the right analytics data) to optimise its pricing. Another example: for an e-retailer, having visibility into stock is an important challenge when it comes to tailoring e-merchandising, adapting SEA investments and product promotion. Today, very few organisations have a clear view of their global data strategy, where data – no matter its source – brings value to all departments who can use it. When considering these global strategies, analytics data – just like sales data, profit data or stock data – is a source of high added-value information for the company – and not simply for the digital department.
What is the main benefit of having expert guidance in your digital analytics strategy?
We first assist with defining a data and analytics strategy before talking about choice of tools, implementation or management. Our added value is indeed to show clients the added value analytics data can bring to different business units. Our challenge is to educate, improve existing use cases, and imagine innovative strategies stemming from digital data sources. An example: decision-making about media purchases and investments can be correlated with stock data to avoid unnecessary spending. In web analytics, we are first and foremost interested in consolidating the omni-channel customer journey to generate sales conversions. In tangible terms, depending on the customer’s history on a website (navigation, contribution, adds-to-basket), certain outgoing phone calls can be extremely profitable in sectors like banking, insurance and tourism, where the average cart value is quite high. Analytics data enables you to detect these behaviours upstream to generate additional turnover and profit. Our role is also to think about questions of data governance; as companies’ data projects generally stretch across their organisations, it’s important to find the right points of contact to help things advance. It’s not always easy!
How can brands make the most of their data during the holidays, sales periods, or Black Friday, for example?
During these high-traffic periods, ad space is of course costlier, so the challenge is investing in the right channels since you cannot be present everywhere. The other important aspect is product availability, and more precisely, the visibility that a company has into its stock. It’s a question of optimising one’s merchandising and campaigns in order to promote the right products and avoid pulling buyers into conversion funnels that are limited by stock. “Drive-to-store” is also a contextual element that should be integrated during these periods of intense purchasing. Many searches are done online and materialise once users are in the store. Lastly, the “real time” parameter is crucial. The example that comes to mind is our customer Sephora during the most recent Black Friday sale. We assisted them through the implementation of real-time reporting; they were able to monitor traffic figures and turnover down to the euro during the entire sales period. They were therefore able to closely track their objectives and react quickly with their online promotions.
What investment choices would you recommend for the months or years to come?
For us, a data lake is an investment to make. It enables a consolidated, silo-free view of all data sources (analytics data included). You can therefore retrieve diverse data, such as call centre data, campaign data, media data, stock data, even competitors’ pricing data, all the way down to weather data. Implementing a system like this requires first defining the high-priority internal use cases, and then building a data roadmap around these key needs. After having worked with many brands, I’ve observed that while all business sectors are asking for this type of system, a company’s digital maturity is a decisive factor in making these types of projects successful.
Any last words to wrap up?
Data is an asset, but it’s not an end in itself. Finding the right use cases requires a mix of good business sense, creativity, project management skills, technology skills, and data science skills. Converting this data into useful knowledge – and ultimately, into money – has been my profession for more than 20 years now. The varied challenges, whether they’re related to business, change, technology or data science, make for a fascinating line of work, not to mention the more human challenge of getting so many diverse profiles to work toward a shared goal!
Happy New Year to everyone and I wish you many new data-centric projects for 2019!