The Client:
Our client is a major car manufacturing company with offices in many countries around the world. The main contractor for this project is a management consultancy company – our partner company in Belgium. Our role in the project was to set up an environment for useful lead management analytics. This would enable the company to make use of the data that is generated on a daily basis.
The Challenge:
The client has a lead generation process in which information is collected from different sources and systems. The goal was to generate a report showing which interactions generate conversions. Moreover, we had to follow the lead journey across all stages of the sales funnel.
The big challenge with this project comes from the unstructured and varied data sets drawn from several different data sources.
Our customer’s sales process:
Our client’s lead lifecycle includes a number of steps. It all starts with lead generation. Leads can be generated from a few sources on the internet, with the main one being our client’s website.
On the website, a customer can submit a request to buy a new or a used car, fill in a request form, or directly book a test drive for a specific car model. Once any of those actions are completed, the customer is classified as a lead and is recorded in our client’s data capture system. A similar process occurs with external marketing agencies. All of this information was required in the report.
From there, the record is sent to the Salesforce Marketing Cloud, where a double opt-in action is triggered. It sends an email or a phone call and the consent of the lead to receive future communication is captured. Once this consent is confirmed, that lead turns into a “qualified lead”. It should be mentioned that there are cases where a lead is qualified automatically on the basis of some legal criteria. Those lead types are also tracked and analysed in our report.
The third step of the journey is to forward the lead to a local retailer who proceeds with the sales process. At this stage, the reporting becomes more complicated because each retailer uses different sales workbenches to manage the leads. The final step is converting the lead to an actual sale. However, in order to achieve a comprehensive overview of the process, our client needed the data for each stage of the lead life cycle analysed and collated in a report.
The Lead Management Analytics Solution:
Before starting the project we agreed on a three-month time period for its delivery. The deadline came from the complexity of the data that had to be managed and of the analytics processes afterwards. We also agreed on specific KPIs that allowed us to shape the scope of the project in a way that would align with the business needs of the client. The KPIs we were aiming for needed to capture the country of the lead, its source, the capturing time period and the generated sales revenue.
We relied on the following technology stack in order to be able to deliver it:
- Azure Data Factory
- Azure SQL Database
- SQL Server Analysis Services
- Power BI
It was impossible to use a plug-and-play tool because of the variety of the data sets and data sources. Added to this, each local re-seller had implemented different kinds of processes and the unified report had to combine everything into one. This meant that we had to gather all the data and structure it into a comprehensive database. So we were able to track the lead journey in every single moment of its life cycle. More importantly, we were able to produce a report that presents a cohesive overview of the sales funnel stages and is easy to understand.
The result:
In the end, we succeeded in delivering a system that on a daily basis, gathers, structures, and analyses data from every stage of the sales funnel. The final reports also serve as a vital tool for our client’s lead management processes. They are now able to easily track where the lead is gathered from, its origin, lifecycle stage, sales revenue and so on.
Enabling effective lead management analytics is just one of the services in our data portfolio. Learn more here – or book a complimentary call with us to discuss your data challenge.
