8 April 2020
Every business today needs one essential piece of kit: a crystal ball. If you could predict the future, risk and…
4 March 2020
By multiplying data sources, predictive marketing can anticipate the requirements of leads and increase the conversion rate. It also rationalises recruitment campaigns.
How can we define purchasing behaviour in our sector of activity? Marketing departments have always tried to answer this burning question with a great deal of market studies, surveys and analyses. Once I have described the behavioural families, I can establish socio-types and undertake targeted actions.
Today, what we call predictive marketing has replaced this descriptive marketing, although there is a certain time lag in the B2C world. As its name indicates, it’s no longer a question of looking in your rear-view mirror but rather of anticipating current and future clients’ requirements so as to deliver the right message to the right person at the right time. This is a particularly sensitive strategy in the B2B world. Decision making can mature over months, even years, but be decanted in the space of a few days. It’s important to be there at the decisive moment.
This anticipation of the purchasing act involves the interpretation of weak signals. Going beyond internal data (CRM, e-commerce website, logistics, client contact centres, etc.) and public data (Companies register, etc.). It involves surveying institutional websites, blogs, forums and social networks, in order to ascertain what is being said about a company. A sort of “social graph” that lets you go well beyond the Industry code (SIC) to characterise the activity of some millions of british companies.
Predictive marketing therefore clearly has a data-oriented approach. Online data collection is automatically performed via the principles of crawling and scraping. Their analysis makes uses of big data technologies, machine learning and semantics.
Research can be carried out on key words, or on a group of emblematic clients, from which the solution will be asked to determine common dominators and, by forecasting, to identify similar profiles. The creation of these “personas” can define the typical actions to be carried out to convert a lead into a client.
In doing this, a predictive marketing strategy does not consist of providing the most leads possible, but in increasing the conversion rate by identifying real potential clients. Once I’ve understood a contact’s intention, I can offer them a customised solution.
Predictive marketing also generates indirect benefits. By hyper-individualising the client relationship, we rationalise recruitment campaigns and therefore their costs. Mass mailings are replaced by less frequent but more targeted mailings.
A predictive strategy can, moreover, optimise purchasing spaces on digital media for the purpose of programmatic marketing.
Still a recent concept, predictive marketing is set to evolve at the rhythm of technological progress. We may imagine that the solutions will soon be able to measure a contact’s degree of influence and their interactions with other leads. A lead could thus supply other leads and a client become “virtually” an advisor.