Intelligent marketing automation: dream or reality?

By Colin Lalouette

Published: 10 November 2024

While automation is certainly essential for addressing big data sets, we also know that personalised marketing is crucial. Can we hope to automate it in a personalised way? Read all our advice on how to use lead generation to improve your marketing actions.
CONTENTS

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The ingredients of marketing automation

An opportunity with big data

Automating tasks saves time, enabling you to prospect a greater number of marketing contacts. The end result is more customers. This approach is all the more tempting in the age of Big Data. The data collected is immense. So much material to feed into the sales pipeline.

The importance of personalisation

Basing your approach on a large volume is tempting, as long as the quality follows. Because the logic of quantity has its limits. Commercial canvassing has multiplied. Over-solicited recipients have grown weary. Mass marketing is a thing of the past, and now it's time to refine the target and personalise the message. But how can you prospect widely while segmenting finely?

Computer intelligence as a solution

This is where machine learning comes into its own. Manual processing of big data is unthinkable. Firstly, because it would be as time-consuming as it would be energy-consuming. But also because it would be impotent and hardly relevant. That's why automatic data processing is so welcome, especially if it's intelligent. Machine learning is a form of artificial intelligence. The machine not only integrates the data, but also the way it is combined and interacted with to produce a continuous analysis. This massive processing results in an autonomous and instantaneous analysis. The richness and history of the panel give the tool a relevant predictive capability. This is known as a learning algorithm.

For more effective prospecting

Better quality scenarios

We can try to predict different user experience (UX) scenarios manually. The idea is to consider all possible scenarios and plan the associated actions. But experience shows that humans tend to idealise the consumer journey. But the customer journey rarely goes according to plan. So "the machine" provides real added value. Because it considers all possible scenarios in an exhaustive and impartial way, a computer programme will be both more complete and more relevant.

The effectiveness of inbound marketing

Deploying richer scenarios makes it possible to implement an inbound marketing strategy. Inbound marketing is about getting prospects to come to you, and generating calls or clicks. This is in contrast to outbound marketing, where you approach your prospects via an outgoing call or email. The appeal of inbound lies in the low cost of implementation in relation to the results that can be achieved. Keeping a blog, setting up a newsletter, having a presence on social networks or providing a white paper are all channels for generating leads - sales contacts. This content invites people to discover your brand and the expertise associated with it. This is known as content strategy or content marketing.

Better qualified lead management

The aim is to address your content in a contextualised way within your scenarios. If you succeed in offering the right content at the right time, there is an 80% chance that a lead will become a customer. To achieve this, the key is to regularly nurture your leads - this is known as lead nurturing - and to monitor their signals of maturity. The fact that a prospect visits your website and downloads your white paper is a positive signal: is this the right time for you to send them a specific email outlining your offer in more detail? These actions, scattered throughout your scenarios, then follow a lead scoring logic.

So how do you go about it?

Careful marketing software

New-generation CRM (Customer Relationship Management) software is based on technology that combines Big Data with machine learning. The result: intelligent marketing automation. This is the case with Plezi, which collects all the information about your prospects, to build tailor-made scenarios for them. This leads application manages the inbound marketing chain from A to Z, automatically and in a personalised way. Connected to your website, the solution will, for example, decipher the last visits of one of your contacts and the articles they have read. This is a qualitative database that you can use to personalise your newsletter: by selecting articles that they haven't read, for example, or themes that are likely to be of interest to them.

Key context data

Plezi respects the confidentiality of its users' own databases and information. Nevertheless, the wealth of content that passes through the solution enables the publisher to carry out cross-analyses. Rendered as contextual data, this information provides user companies with a benchmark to situate their performance relative to their sector. The application can also make suggestions on operational issues such as when to send content and at what rate. Based on the success rates observed for the actions carried out by each user, Plezi is in a position to guide each of its users, so as to optimise the impact of their marketing strategies.