PSV Business Leads

Project description

The marketing intelligence department of PSV wanted to know if there were any business opportunities to be found in the fan database. This was because there was a significant drop in the amount of business connections over the last couple of years.
PSV provided the Datalution team with some datasets about the business to business contacts, fandata and sales data. With these datasets the team started working on the project. The project scope was set on a list of companies that could be potential business leads for PSV.
To reach the end goal of the project the team went through the PPDAC cycle. PSV came up with a problem. The Datalution team sat down with Joeri Verbossen and their coaches and created a plan. PSV provided the data and the team could start the analysis. In the last phase the team came with a conclusion and a list of potential business leads for PSV.

Context

The main research question is: Can we identify business opportunities in PSV’s fan base data?
The Corona pandemic hit many companies hard. PSV noticed this as well when the business seats in their Philips stadium were turning up empty and business relations were pulling out. Now that more people are vaccinated and the Dutch government is easing constraints on events, PSV is looking to regain and perhaps even expand their business unit.
Before investing in expensive and time consuming campaigns to attract business leads, the marketing management of the football club would like to explore what can be done using internal data. A lot of customer data is collected when fans buy tickets for matches, log onto their account or even buy merchandise. The objective given to the DDBL students was to find business opportunities within this data. By getting insights in the purchasing behaviour of fans, a list of prospects can be drafted. For example, by looking at the frequency of ticket purchases and the amount of money spent.
Insight in customers can also be used by comparing it to a persona, the imaginative, ideal customer. When a customer matches this persona and is therefore a prospect, they can be targeted more effectively.
By collecting, cleaning and analysing the fan data collected by PSV, correlations might be found. If so, a list of business prospects can be drawn. In this way, companies on that list can be targeted more personally and more effectively. Hopefully resulting in new partners and filled business seats.

Results

Since the goal of this project was to come up with potential business leads, the final form of the result is in a list. This list is ranked with a score on total Customer Lifetime Value. This score consists of 3 factors: Recency, Frequency and Monetary value. All companies in the database that do not have a business seat in the football year 2020-2021 occur in this list if they have bought seasonal tickets in the 5 years prior to this season. The idea is that companies who buy frequently, have bought recently and for a relatively large amount of money are better customers than companies who don't. By valueing these companies by taking all three factors into account, a list with the best business leads is made.

About the project group

All participants in this project have a background in business, with different specialisations. Studies include International business, industrial engineering and commercial economics - digital business concepts

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