Data management is a major concern for business leaders. Much more than a simple concentration of information on contacts, the data files that you keep preciously allow an optimal marketing and commercial approach of your prospects …

The recent entry into force of the General Data Protection Regulation (GDPR) calls into question many of the practices used in the processing and analysis of data collected by companies. New professions, tools and new techniques have appeared. So it’s no coincidence that today we’re no longer talking about big data, but smart data.

Training & Co'm

Make all employees aware of data management

Articles 32 to 35 of the GDPR created by the European legislator make the manager aware that managing data is above all a collective mission. The famous DPO (Data Protection Officer) is the guarantor of the transmission of good practices and also the main asset for the management of his data.

Learning to handle data well begins with training employees to process information. Awareness allows all the stakeholders of a company to ask themselves the right questions. Have I properly secured my contact database? Do I really need all the information on a form? How should I process incoming data …?

Performing an internal audit of issues related to data management is a first step. Raising awareness of each employee is therefore essential to manage data effectively.

Build a smart data strategy

A company can collect countless amounts of data in a year from different sources. To properly manage these flows, it is essential to introduce a flexible data processing strategy adapted to all functions. Long gone are the days of the address book on the corner of the desk. Today, data must be collected, updated and accessible to all teams.

To achieve this, you must identify the data that is necessary for the development of your business. Thus, each pole must know the information useful or not for its activity. For example, does the salesperson need the prospect’s IP address that he has on the phone? Obviously not!

Here are some examples of useful data for different functions of a business:

  • First name, last name, professional email, business phone and company name: these are the basics for marketing campaigns and the prospecting phase;
  • IP address and other metadata: useful for analyzing the performance of a digital strategy, it is however advisable not to extract this information;
  • Address: professional or personal you can do without it.

BtoB or BtoC, data is the nerve of the war, but no need to have too much. Internally, you must know the path traveled by each data in order to benefit from it. According to a Sparklane survey, for 77% of salespeople updating data about a prospect helps reinforce their speech.

Define an internal data processing and analysis process

Here we are, the most complex mission in data management within a company. Even in the best structures, it’s easy to lose or have wrong information (in fact, imagine the amount of information collected by Amazon). It is therefore advisable to set up a clear and precise task process. First identify each actor involved in each of the data. Then delegate the processing to a competent person. The creation of the data analyst profession may be the solution. Finally, constantly update the data in your possession, the recommendation is to automate it as much as possible.

As registered in the GDPR, each company that processes personal data must schematize the management. To do this, you can rely on online software like Lucidchart accompanied by a simple Excel workbook. Regarding the risk analysis of the data collected, the free PIA (Privacy Impact Assessment) tool put online by the CNIL is very comprehensive. He can thus assist you in the development of an internal methodology.

Use digital tools adapted to your needs

Data management must be done quickly and efficiently. To do this, you need to equip yourself with tools that allow your business not to be drowned in the mass of information. To facilitate exchanges between your different teams, you must set up a complete CRM (Customer Relationship Management) software. Indeed, tools such as Salesforce, Hubspot, Marketo or Plezi are very useful for managing and securing the data in your possession.

In data management, operational efficiency is a key issue for a profitable return on investment. This is why using online platforms like Google Drive, One Drive, Trello or Slack is highly recommended. You can thus store and share internally all the resources essential to your activity. No more emails exchanged between the marketing and sales department for prospect files.

Make a complete assessment of company data

Once all of this advice has been put in place within your company, you must punctually perform a complete analysis of your data. A review 2 to 3 times a year is good practice and allows managers to have visibility into the health of data. To start, assign one or more people internally to this assignment. Note that it takes around 160 hours of work for a single report in an SME.

To create effective reporting, here is a checklist for a data analysis project:

  • Centralize on a file (Excel workbook for example) all the data collected for the analyzed period (3 months, 6 months or even 1 year);
  • Remove unnecessary information for your business, duplicates or erroneous properties;
  • Segment the data according to your objectives (a target of prospects, the customers of a product or a service, the geographical area …);
  • Identify missing information (email, first name, last name, company, etc.);
  • Update your database and your CRM;
  • Plan the actions to be carried out over the coming months;
  • Share the actions taken with all of the employees (everyone must be involved, to come back to the first tip).

Data management has become a crucial issue for all companies. Much more than a simple task in an agenda, data represents a real function. The appearance in the 2000s of Big Data gave birth to many fantasies for leaders. Knowing everything and knowing everything about prospects seemed like an oasis in the desert. However, today, the overflow of data forces companies to implement a real strategy. The latter is based on the advice cited in this article.