Motivaction and ADC have joined forces in a partnership. Motivaction is a leading market research agency known for the value- and motivation-based segmentation model “Mentality”. ADC is a data & AI Consultancy offering services to many industries, including the financial sector, public sector, and healthcare. With this partnership, we aim to break the barriers between market research and data science in multidisciplinary teams to deliver the best and most actionable insights for organisations.
Karel Slootman, Commercial Director of Motivaction, and Hans van Avendonk, ADC Country Lead, the Netherlands
Converting data into business value
Both ADC and Motivaction deal with data on a daily basis: ADC with organisations’ data and Motivaction with market research data. The connection between data, AI, and market research is hardly addressed in many organisations since market research and data science are often viewed as separate domains, rarely intertwined. However, both market research and data science come with inherent limitations.
By bridging these fields, Motivaction and ADC convert their data into business value for their clients.
“We are at home in the analysis and translation of survey data into solutions for customers. Therefore, ADC’s experience and knowledge in the field of data science and data engineering will be a valuable addition to our expertise.”
-Karel Slootman, Commercial Director of Motivaction
What does this partnership bring?
Bridging the expertise of both parties provides richer insights. Gaining knowledge about people’s values and motives with the help of the Mentality model is the key strength of Motivaction. ADC then implements this information into organisations’ systems and strategies. This increases customer knowledge, which has an impact on customer service and, as a result, on the relationship with the customer.
“Ultimately, the customer experience improves when we merge our knowledge. In our collaboration, we make the insights and data predictable, imaginable, and usable. We bring in-depth insights from customers with the help of Mentality and data.”
-Hans van Avendonk, ADC Country Lead, the Netherlands
By bringing ‘the customer’ to life in organisations, employees get a clear and understandable picture of the customers. This irrevocably helps to improve the connection and not only increases the trust, but also the loyalty of customers. Moreover, it contributes positively to the job satisfaction of employees. An employee who is better able to help or serve customers by using the insights that data brings, gets more satisfaction from work.
Use Case 1: Improve Customer Experience
Our partnership can be used to enhance customer experience (CX) through personalisation. Market research employs surveys to segment customers, providing insights into customer identities. However, translating these insights into action can be challenging.
On the other hand, data science predicts customer segmentation based on observed characteristics, offering an understanding of customer behaviour. Yet, it is limited to what can be measured from observed behaviour.
When combined, we can train a prediction model that combines the customer segmentation with observed characteristics to determine the “type” of customer for every new website visitor. This approach allows for a comprehensive understanding of your customers and their online behaviour, enabling personalised content delivery. By doing so, your organisation can enhance the customer experience through effective personalisation.
Use Case 2: Enhance and Assess Customer Satisfaction
To enhance and assess customer satisfaction, consider combining two approaches. Market research employs highly personalised surveys to uncover detailed pain-points, providing a comprehensive but non-scalable view. On the other hand, data science utilises Natural Language Processing to analyse call transcripts from the client contact center, offering a large-scale perspective, albeit potentially superficial.
By merging these methods, you gain a complete 360-degree view of pain-points, allowing for targeted problem-solving and recognition of successful practices. This integration empowers your organisation to enhance customer satisfaction and streamline client contact processes.
Use Case 3: Determine a Pricing Strategy
Consider the application of these methods in determining pricing strategy. Market research utilises surveys for conjoint analyses, establishing a theoretical “best” price based on willingness-to-pay. However, this willingness-to-pay may differ from real-world interactions. Data science, on the other hand, learns from observed customer behaviour with existing products, aggregating insights from the past. Yet, the implicit assumption that new products and services are identical to previous ones can be incorrect.
By merging theoretical client willingness-to-pay with real observed customer behaviour, organisations can pinpoint the optimal pricing strategy. This approach combines theoretical price determinations, aggregates historical data, and tests hypotheses and assumptions to ensure the theoretical price aligns with practical outcomes.