Common CRM dissatisfaction
Numerous businesses state they are dissatisfied with their CRM technology – a core part of modern business software – but the issues can often be found in the processes and data rather than the technology itself. It can be seen as an easy option to blame the CRM tech rather than addressing the root causes of problems within existing processes and data quality. Business leaders can often fall into the trap of thinking an investment in tech is a solution rather than a tool to achieve success.
Successful CRM projects must deliver quantifiable outcomes that help organisations improve revenue, reduce risk and cost, and build intangible brand value. This means a focus must be placed on strategic outcomes to understand and generate true value.
There is a need to educate users from all levels of the organisation on the importance of addressing issues with processes and data before implementing new CRM technology. In Salocin Group’s experience, a slowed down, strategy led, data fed approach to CRM implementation leads to a faster rate of achieving objectives and success once it is set up and running.
Data leaders must stress the importance of taking the time to understand and fix underlying issues before rushing to deploy new technology, which in itself is not a solution, but instead a tool to be used as part of the solution.
Alignment is crucial to success
Simply put, executive alignment on priority outcomes and the reasons for change are the bedrock of achieving CRM success. Data leaders and their teams must ensure all stakeholders understand that the project cannot be pulled in different directions because the overall success of CRM integration, based on clear operations and clean data, will benefit everyone in achieving their own objectives.
“Our methodology involves running two parallel work streams: a data work stream and a strategy work stream,” said Alex Holt, CRM Strategic Consulting Director at Salocin Group. “The data work stream focuses on understanding and improving data quality, while the strategy work stream focuses on aligning processes with the desired outcomes.”
- Data work stream: The data work stream involves understanding the current data, identifying data gaps, and establishing data governance to ensure data quality and security. This work stream is essential for building a strong data foundation for the CRM project.
- Strategy work stream: The strategy work stream focuses on understanding the current level of sales maturity, drilling into processes, and ensuring that the CRM will support the desired outcomes. This work stream involves identifying regional variations and areas of excellence that can be used for testing and delivering proof of concept.
A core part of achieving alignment is understanding the issues at hand and defining what people are seeking to address.
Customer churn prevention
A recent client of Salocin Group – a global chemical and material producer and supplier – approached the Edit team with concerns about decreasing customer retention. The client sought solutions to reduce the amount of churn taking place and instigate actions that would improve the quality of their data processes.
Salocin Group began with an approach of unpicking the granular issue and then evaluating customer behaviour for this client’s niche market.

“We’re defining what churn actually means for the client initially, which might seem obvious, but the challenge has been to define churn at granular level,” said Marc Dallimore, Data Science Practice Director at Salocin Group. “We go as granular as the business size of each customer, to see what churn really looks like rather than setting a blanket rule. We then delve deep into understanding how these customers behave. In this instance, we knew what we were looking for due to our experience in this particular vertical and with our experience of defining and supporting B2B retention strategies.”
A step-by-step process was then followed to create a customer churn prevention model, which would provide necessary answers to important questions, while delivering clear communications and outcomes to the organisation throughout the process:
- Identify key stakeholders within the organisation.
- Engage with these stakeholders to understand the specific business area, expectations, customer journey, and planned churn prevention approach.
- Analyse historic churn work to understand what has or has not worked before; make recommendations for refinement based on new findings and prior experience.
- Review the churn definition to make sure it is appropriate for each use case and then revise it further to align with specific business goals. This process includes defining the life stage of new, active, and at-risk churn customers.
- Identify available data sources.
- Collect and clean available data to align to the base churn model file.
- Determine the information value of each data source.
- Develop and refine predictive variables to enhance model performance.
- Build a predictive model using the most appropriate modelling technique based on what is available, ensuring transparency and explainability for all stakeholders.
- Present the model and supporting data in a visual dashboard.
- Acquire stakeholder review and feedback.
- Consider feedback on the implementation.
- Run the deployment and automation.
- Continue monitoring for success.
When it comes to testing and delivering proof of concept, Dallimore explained: “We start with a proof of concept to test the effectiveness of the aligned outcomes, which involves testing a line of business, region, or sector to measure the impact before a wider rollout.”
Results of this approach
The example provided by Salocin Group is, at the time of writing, is in the proof-of-concept stage, which has seen adoption in two main business areas of the client. Following the results of this stage, it is hoped the solution will then be scaled across all regions and business units.
“So far, we’ve made great progress in saving time for the sales reps and have already demonstrated that we are raising insights they previously didn’t have,” said Dallimore. “It means the sales and customer loyalty teams can fully identify clients at risk and put a plan in place to save them from churning. Long term, this will also support the business in making a financial saving without having to invest in as much time and manual effort.”
By taking the time to truly address the inherent issues behind implementing CRM, such as data quality and ineffective processes, data leaders and their businesses can achieve long-lasting success. CRM technology should not be seen as a solution but instead a tool to achieve objectives, whereas business alignment, clean data, and well-understood processes are the true bases for achieving success.
To see how Salocin Group can assist you on your data journey, contact J Cromack.
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