Data-driven in B2B Marketing: advantages, obstacles and best practices

Interview with Fabio Lazzarini, International Business Information Strategies Director @CRIF

Fabio Lazzarini
International Development B2B Services Director @CRIF

In a context where B2B customers have the same expectations as B2C consumers, the responsibilities of Marketing for business results increase, given its leading role in gaining in-depth knowledge about the buyers and their needs.

Everyone is talking about the importance of analyzing data and making decisions based on it, but few have really understood how to do it, and how a data-driven organization should be structured.

Let's delve deeper into the subject with Fabio Lazzarini, International Business Information Strategies Director of CRIF, with five years of experience in the world of business information and business intelligence. 

 

Q: Hello Fabio! What do you mean when you say you use analytics to become smarter? Can you explain how the transition from hindsight to foresight happens?

A: As I graduated in Statistics and I’ve always been involved in data, analytics and business intelligence in my career, I am very happy with the increasing attention that is given to data science, big data, analytics, etc.., especially in recent years.

It seems to me, however, that the approach is often very "muscular" and limited to emphasizing the amount of data or the processing speed. Instead, in my opinion the most interesting and useful aspect for companies is changing decision-making processes, making the intelligence extracted from data more pervasive and effective.

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The concept of hindsight effectively describes our capabilities when we stick to using descriptive reporting that looks to the past, often limited to measuring performance. Examples in companies are abundant, such as quarterly earnings reporting.

This type of analytics implies a delay on the reporting period (e.g. the half-yearly revenues available in September), which limits their effectiveness in terms of real decision support. The next step in the ideal evolution of business intelligence is predictive analytics and insight, i.e. the vision of future consequences of business decisions.

The arrival point is precisely foresight. It means using advanced analytical tools, which allow you to optimize your decision-making processes by simulating different future scenarios and optimizing the use of resources.

To sum up, analytical tools can be divided into three categories:

  • Descriptive, which answer the question "What happened?" and therefore linked to the concept of hindsight.
  • Predictive, answering the question "What will happen?" and therefore linked to the concept of insight.
  • Prescribers, who answer the question "What should I do?" and therefore linked to the concept of foresight.

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Q: What obstacles prevent companies from becoming data-driven? How does a successful data-driven organization work?

A: The first and most obvious obstacle is not having adequate technology. At the same time, it is important to understand that technology is not the only lever available. Quality data is paramount and the old motto garbage in-garbage out has perhaps never been as topical as it is now.

Poor quality, outdated or not-fit-for-purpose data seriously affects the way information can be used; as a consequence, inefficiencies increase and customer relationships and business performance suffer too. The quality of data is crucial for companies that want to base their decisions on it.

The third and main obstacle, the one which leads to the failure of any data-driven strategy, is organization itself. “Political” and management problems are often the biggest barrier. To overcome it, the entire company must be involved in the implementation of the strategy, including all users, who must be properly training, starting with the top management.

If you want to build a data-based organization, the data culture must be pervasive: data must be transparent, and everyone within an organization should understand how the company works,  and have the possibility to make an impact.

If we were to summarize everything in one slogan, a modern business should be powered by data and driven by people.

 

Q: Can you briefly explain what you mean by Account Based Marketing? Why do you think it leads to better alignment between Sales and Marketing?

A: Account Based Marketing is a strategy used by B2B marketers to reach a group of very targeted prospects. In other words, instead of focusing on sales and marketing strategies aimed at a large group of companies, the message is directed precisely at a single prospect. Basically, it's about moving from a one-to-many approach to a real one-to-one approach.

The idea is not entirely new and is often used as a buzzword. In the past, it used to be seen as a laborious, costly strategy reserved for large companies that could afford to target only a handful of their largest accounts.

But with today’s technology, data availability and data analysis, ABM can be used on a large scale by any business (that doesn't mean it has become easier to run, though).

The first key point for the success of such a strategy is the alignment of Marketing and Sales. The M in the acronym ABM should be removed, because once this strategy is implemented correctly you should not be able to tell where Marketing ends and Sales begin. In order to create this synergy between teams, you need shared processes, shared data, and shared insights and measurements. In many companies, for example, Marketing teams are measured on closed contracts, not on generated leads.

To do this, Sales and Marketing need to be structured so that they can easily collaborate. It is important to overcome traditional silos, encouraging a comprehensive view and agile, cross-team actions, which eventually lead to better customer experiences.

It's a real cultural change, from old lists of “more or less hot” prospects to approach with “cold callings” to a truly customer-based approach.

In short, these are the necessary steps:

  • Marketing actions that can create engagement and a relationship with prospects
  • Targeted and timely data that describes and predicts the purchasing behaviors of the potential customer
  • Alignment of Sales and Marketing to simplify processes and increase effectiveness