Visable 360
The B2B magazine for digital sales
Visable 360
The B2B magazine for digital sales

“If you can read data, you can understand the customer”

Customer behaviour in the B2B segment has changed in the past few years. Interested potential customers remain anonymous in the buying process for longer, until they contact sales. Which is why data-driven marketing is more important than ever.

Lutz Klaus, founder and owner of Marketing ROI Consulting, has been concerned with the advantages of data-driven marketing  for quite some time now. His book Data-Driven Marketing und der Erfolgsfaktor Mensch (Data-driven marketing and the human success factor) was published by Springer Gabler Verlag in 2018. In an interview, he reveals how the captured data can be used, which measures companies should initiate, and why the separation between B2B and B2C is becoming ever more blurred.


Colleagues talking about data


Mr Klaus, which essential benefits does data-driven marketing provide?

Data-driven marketing helps to take better decisions and to create the conditions for success when it comes to digitalisation. To a certain degree, all companies act in a way that is driven by data. However, this often takes place using outdated data. It is as if they were driving a car while looking through the rear-view mirror.

On top of this is the fact that decisions are frequently taken based on personal experience and a good feeling. “Data-driven” means collecting objective data in a targeted way, analysing and using it to improve the decision-making process and to scale business through automation.

This has come about due to changed customer behaviour over the past years. The buying process is taking place more and more anonymously, until the interested person contacts the sales team. Analysists speak of up to 70 per cent in the B2B segment, and even 100 per cent in e-commerce, which is growing by two digits every year. In extreme cases, we may never even personally meet our best customers.

Data gives us back this contact. The data shows us, based on digital body language, what the customer likes and what they don’t like. This also strongly affects sales. CRM (customer relationship management, sic.) becomes CDM – Customer Data Management – in my opinion. If you can read data, you can understand the customer. Customers expect that you also know them online, speak to them personally and adjust content to meet their needs. In a survey, more than 50 per cent of those questioned confirmed that they would leave a supplier if the supplier is not able to do this. For companies, this means that they have the potential to lose half of their customers – or to win over customers from competitors who do not invest in data-driven marketing.

Can you explain this in more detail using a concrete B2B example?

Experienced sales staff knows how to read important buying signals in the body language of the potential customer. Data-driven marketing recognises customers concrete interest based on their digital body language. It can identify customers through targeted activities and qualify them for direct contact by the sales team.

Data-driven marketing helps companies understand which measures are effective. Through consistent measuring and optimisation, channels, times and content can be optimised. Do we really need another brochure or have to have a booth at a trade show? What do Google Ads, LinkedIn or Facebook really do for us? Instead of implementing a number of activities, data-driven marketing helps to filter the most effective measures. Through the use of methods such as figure and driver trees, the influence of the marketing activities on sales success can be made transparent. What’s more, decision-makers can use objective information to simulate which measures lead to better results.


Data-driven marketing recognises customers concrete interest based on their digital body language. It can identify customers through targeted activities and qualify them for direct contact by the sales team.

How do companies then get the data they need, and how can the data be processed in such a way that it goes from being “big data” to “smart data”?

There are four data sources: generated, received, paid and public data. The first group includes data which companies themselves generate or have captured, and then provide for processing. An example is product information from installed machines. The second source covers data which we receive from our customers and partners. This includes address data in CRM or the purchasing history in the ERP (Enterprise Resource Planning, sic.). Paid data comes from third parties for a fee. This calls to mind affiliate marketing or comparison portals like Check24. Public data comes from Wikipedia, standard weather forecasts or GPS data and is available to everyone.

Before we think about the data source, however, we should first clarify how it is going to be used. This is the first step to developing a data strategy. I’m not convinced of the idea of first collecting data and then thinking about what to do with it. Companies should start with their goal and then think about which data they need. Do they need to increase sales or lower costs, boost productivity or customer loyalty ? As soon as this has been decided, they then need the required methodology to develop the initial data-driven applications. One of the methods I apply is Canvas models from the company Datentreiber, in workshops with the relevant stakeholders.

Which measures must a company initiate in order to be able to pursue data-driven marketing?

It all starts with a decision from management to implement this approach consistently. Data-driven marketing is not some short-term project, but a long-term strategy for being successful in digitalisation. It is also not some single department initiative, but a cross-departmental topic for the entire company. This involves the necessary investments in staff, qualifications and technology.

The staff take top priority for a reason, since many initiatives fail due to lack of adoption and a debilitating corporate culture. In my book Data-Driven Marketing und der Erfolgsfaktor Mensch, the readers discover seven key factors and core competencies for future marketing and how to put these into practice.

My proposal: 20 per cent of the marketing budget should be allocated to analytics. And naturally IT plays a leading role here. Before we talk about tools and technologies, I can only stress once again how important it is to be clear of what the goals are from the beginning. To implement this new way of working, and to establish a data culture, I recommend working with external experts whenever needed who have the necessary experience. Internal change often requires external impulses.


Lutz Klaus, founder and owner of Marketing ROI Consulting

Lutz Klaus, founder and owner of Marketing ROI Consulting

Which characteristics should be paid attention to when it comes to data-driven marketing in the B2B segment?

Firstly, I believe the separation between B2B and B2C to be disappearing more and more. In the end, both are about people. In light of this, the essential difference is a more complex buying process, which is seen in longer cycles and a larger number of decision-makers.

This development is being faced by many companies with the introduction of marketing automation, which in my viewpoint represents a good starting point for data-driven marketing. Based on this, the implementation of an own data strategy should be systematically developed further. This leads to the core competence – and here it is not about choosing solutions off the rack, but a tailored approach.


Before we think about the data source, however, we should first clarify how it is going to be used.

Many companies have an aversion towards data handling, as privacy policy regulations are becoming tighter and tighter …

This is the wrong thing to do; it can have consequences for one’s livelihood in the long term. Customers want relevant content and continue to be interested in contact with companies. Here, the name of the game is about tapping into the realm of possibilities as much as possible – in close cooperation with privacy policy experts.

Let me explain this using another example: I don’t go to an accountant for him to explain all the things that are not possible, but instead to help me reduce my taxes within the realm of the legal possibilities. The same principle should also go for data protection and its officers. 

How can the data collected and segmented be optimally leveraged in advertising measures? Can you explain this using an example?

By making sure the measures are tailored more and more strongly to individual needs, in terms of channels, content and times. If you take the leading digital platforms, each page is personalised. That’s the benchmark. A concrete example for campaigns is the use of so-called PURLs. These are personalised websites on which only relevant information appears for the visitor. In addition to a personalised salutation, as well as the name and telephone number of the responsible account manager, offers are communicated in line with customers’ needs. Nowadays, videos or holographic illustrations of products need to be produced just once and can be personalised in the thousands. Personalisation leads to better results if the data base is correct.


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Where do you see data-driven marketing in five years? How will it change and develop further?

Data-driven marketing will differ from normal marketing in future too. It is always about finding customers, keeping them loyal, developing them further and ensuring a measurable EVA to achieving the company’s goals. Data-driven marketing can be an incubator for the successful digitalisation of an entire company – up to data-driven business. For marketing, this is a huge chance.

I am increasingly seeing the trend towards dissolving traditional department structures and organising cross-functional teams according to market segments or topics such as customer loyalty. Today, applicants have hardly a chance to get a job in marketing if they do not have any digital experience. In a few years, this will be a prerequisite. Data competence, in combination with analytical skills, will take the place of digital competence.

By the way, this also goes for other sectors, not just marketing. We will most likely see a broad use of advanced technologies, including AI. Centralised platforms with customer data will then form the foundation. In addition to the use of standard applications, individualised technology stacks will become a competitive advantage for being able to act precisely and quickly on the market. I still remember the statement a digital company once made: “I would like to have an idea in the morning that is on the market in the afternoon.”


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