Route to data-driven (co-)working


  • Customer case
  • Data Analytics
  • Data projects
Zev Posma
Business Manager
3 min
17 Jun 2020

DIGIWEDO specialises in designing and developing responsive websites, web shops and web applications for SMEs (MKB). They regularly receive questions from customers about how to collect, visualise and/or analyse data in the right way. DIGIWEDO does not yet offer any services in the field of data. They asked us to think about how they could expand their existing services when it comes to advice in the field of data-driven working. Within a week, using our data pressure cooker we proposed a clear plan that helps DIGIWEDO to meet customer needs.

Our approach

It was important to understand DIGIWEDO's customers and their problems, so that we could align the propositions properly. We applied a method that is widely used in sales and customer experience teams: the Value Proposition Canvas.

Value proposition canvas
DIGIWEDO was previously known as OnlineVisual

The following elements are important in the customer profile (right side of the figure):

  • Pains: what problems do customers experience?
  • Gains: what would they like to get out of it?
  • Customer Jobs: what would they like to be able to do?

After filling in the canvas, we started working with a multidisciplinary team to develop a proposition that fits this customer profile (left side of the figure).

The team consisted of 3 specialists: a Technical Web Analyst, a Data Analyst and a Customer Experience Specialist. The reason we worked with different specialists is because DIGIWEDO's customers are often still at the start of data-driven work. They therefore need assistance in every part of this process.

But how do you ensure that smaller companies, often with little data and traffic, can still start working with a data-driven approach? This requires that you follow the right route to data maturity, as described in our Building Blocks Model: from setting up Key Performance Indicators (KPIs) to improving the customer experience.

The result

The result of the data pressure cooker was a working document with explanations and propositions for DIGIWEDO that they could offer to their customers. With us as a data partner, they can expand their services.

The propositions are three tailor-made packages that depend on the size and complexity of the customer. These packages are structured as follows:

1. Inspiration & knowledge

Focuses on one-off sessions and training at the customer. E.g. inspiration sessions or training, but also Google Analytics Audits or Privacy scans.

2. Basics

Basic customer support in the field of data. This includes implementations in line with the market, setting up and maintaining tools, answering questions and delivering requested analyses.

3. Advanced

This package focuses on in-depth analysis and optimisation. Components of this can be: proactive analyses, user testing, gaining insight from multiple sources, customer journey analyses and the creation of personas.

We then filled in these packages for the five knowledge domains, increasing in data-driven maturity, in line with our Building Blocks Model:

  • KPIs
  • Measurability & layout analytics
  • Analysis and reporting
  • Conversion Rate Optimisation (CRO)
  • Customer Experience optimisation

We combined the proposition packages and the knowledge domains in a proposition matrix. We presented this on the last day of the data pressure cooker to DIGIWEDO. Theywere very enthusiastic about the possibilities that we can now offer together to their end customers.

Want to know more?

Zev will be happy to talk to you about what we can do for you and your organisation as a data partner.

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