How can you optimise your marketing with a data-driven strategy?

Faced with the challenges of Big Data, companies need to improve the way they collect and process customer and prospect data. Necessary for improving the performance of marketing campaigns, a data-driven strategy is the secret of success for modern businesses. However, using massive amounts of data can bring with it a number of day-to-day challenges. We explain how to implement a data-driven marketing strategy, without losing your head!

Why is data-driven marketing strategy important? 

DEFINITION OF DATA-DRIVEN MARKETING

Faced with an ever-growing volume of data (the "Big Data" era) many companies want to make the most of the data they collect on a daily basis. This is made possible by a data-driven marketing strategy which involves collecting, organizing, analyzing and interpreting digital data.

The aim? To enable product/marketing teams to make strategic decisions in line with customers' expressed needs!

THE BENEFITS OF A DATA-DRIVEN STRATEGY

Today, data is the source of all decisions: out with the guesswork in with the facts! As a real added value data is used to increase the profitability of marketing actions.

Mastering data is particularly useful to:

• Optimize the user experience on all the company's digital platforms (website, social networks, etc.).
• Create the right products and offers for your customers, exploit new market opportunities, and thus increase your sales!
• Offer a personalized customer experience, based on online consumer preferences.
• And, of course, boost your results: number of customers, sales, net margin, etc. 

MARKETING DATA & PERFORMANCE

Prerequisites for a successful data-driven marketing strategy 

Before deploying a data-driven marketing strategy, keep these key success factors in mind:

• High-quality marketing data
• Targeted, segmented customers
• Clearly defined objectives and KPIs
• Collaboration between the company's various departments (marketing, sales, communications, etc.) to optimize the positive impact of the data-driven strategy. 

How to implement a data marketing strategy? 

#1 - SET OBJECTIVES

The first step in your strategy is to identify, prioritize and formulate clear objectives before collecting marketing data. This will enable you to select the data you need to collect to reach your goal. Without this, you risk spreading yourself too thin (and that's expensive!).

#2 - COLLECT DATA

Here, you'll need to identify the data sources available within your organization. Today, these are scattered: contact forms, newsletters, promotional emailing, prospect and customer CRM or data from platform marketing tools (Meta, Google, LinkedIn, etc.).

GOOD TO KNOW

Focus on data quality, not quantity!

#3 - SORTING AND ANALYZING MARKETING DATA

You've collected all your data? Good job, now it's time to format and reconcile the data from different sources. Clearing up duplicates and ensuring consistency between formats! Only then will you be able to analyze the data using the KPIs set up in phase 1.

To find out more, discover 6 questions to understand everything about marketing data.

GOOD TO KNOW

For greater efficiency, opt for marketing tools that enable you to automate your marketing actions. It's an essential time-saver! In the data-driven approach, this is called "building your Martech stack".

Data-driven marketing strategy: what to look out for? 

Have you been seduced by the data-driven approach and want to implement it within your company? Excellent decision! But it's better to be safe than sorry... so take into account the main challenges you'll face.

1/ Resource management: today, your marketing data is probably scattered and difficult to access. You'll need time and a team to collect, process and analyze it. 

2/ Data maintenance: keeping your data up to date is expensive, both in terms of time and money (server costs, tool subscriptions, dedicated team, etc.). So you need processes in place.

3/ Data confidentiality: this is one of the biggest challenges facing organizations handling large volumes of data. You need to ensure data security, to avoid the risk of data leakage!

Knowing how to work with data is a job in its own right. Companies therefore need to recruit the right profiles, who can also integrate artificial intelligence (AI) to gain in efficiency. If you're interested in this field, come and train with us!