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The outbreak of COVID-19 has a significant impact on the European economy. Trade fairs in particular suffer from the effects. In the entire DACH area there are currently countless cancellations and postponements. If they do take place, however, the visitors are usually not coming. This is a problem for all those companies that use trade fairs as a platform to make business contacts and generate leads for sales. In this article you will learn which alternative methods will deliver the missing leads - data-driven and in a captivating quality.
In the entire DACH region, there are countless cancellations or postponements of trade fairs and exhibitions. Switzerland has in any case already banned all events with more than 1000 participants.
Those trade fairs that nevertheless take place have very low visitor numbers. Although many have booked their participation, they cancel it at short notice, often up to 90%.
The consequences are serious for many companies and above all cannot be planned. Trade fairs and exhibitions are currently cancelled only a few weeks or even a few days before they are due to take place. When companies plan a fixed number of business contacts and leads, and then fail to generate them in the short term, this is a problem.
The absence of visitors to the trade fair booth poses a major problem for marketing. Companies use this platform to establish contacts with potential business partners and to promote their products. However, as is well known, presence at trade fairs is not the only way to generate leads. There are many other methods, some very effective from the world of data. One variant is the so-called Twin Analysis, which searches for ideal customer profiles in the data universe. Another - probably even better - is Smart Data Analytics. In detail, these two are about the following:
This method, also called look-a-likes, begins with a master data cleansing. It corrects incorrect information in the database such as incorrect addresses or contact persons, fills gaps and eliminates duplicates. In the second step, all data records are enriched with additional information such as industry, company size, turnover, etc.
In the third step, a segmentation of the companies in the CRM is carried out on the basis of the previously enriched information. The aim is to find out what the ideal or typical customer looks like. How big is the company? In what industry is it doing business? How will it develop in the future? The segmentation makes similarities and patterns in the customer base visible. This is also called clustering.
Now comes the decisive and final step. A data specialist like Bisnode builds the model from segmentation across the entire data universe, looking for companies that have the same or similar criteria as the top customers in the CRM. This generates a list of potential customers and the basis for campaigns or for transfer to a call centre.
Smart Data Analytics delivers lists of high quality B2B leads within weeks. The quality becomes even better as machine learning is an integral part of this lead generation method. The findings, i.e. how well the leads perform, are fed back into the model and make it even more intelligent.
How does Smart Data Analytics work in detail? This requires data from various sources: The company's own from the CRM, enriched data from Dun & Bradstreet's worldwide largest data universe with over 330 million entries, and crawled information from the internet.
Based on current topics or key terms, Smart Data Analytics generates lists of companies that are highly likely to have a real need for certain products at the moment. The result is a set of highly qualified marketing leads. Just how well this works is demonstrated by Messe Frankfurt. The share of high-quality leads there rose from 16% to 90%. It is logical that the sales department is extremely happy with it.