Most organisations store vast amounts of information about their customers in transaction systems such as their billing and CRM systems. They are also constantly surveying customers for their feedback and recommendations as well as drawing on customer insights from social media and other external sources. By Integrating all this data, brands hope to build a more complete and unified picture of their customers.
There are numerous reasons for organisations wanting to do this. The primary reason is to better understand customers and their behaviour which can translate into more sales, lower cost to service and increased customer loyalty and engagement. Brands that can master the management and use of customer data can also offer hyper personalised service and experiences, providing a significant competitive advantage.
Lisa Khatri, head of customer, brand & design experience APJ, for Qualtrics, who classifies customer data into operational data (from ERP, CRM and other transaction systems) and experience data (from customer feedback and satisfaction surveys), comments, “By integrating customer feedback – the experience data – with operational data, businesses and governments benefit from comprehensive and valuable insight into how the organisation is performing, and more specifically the reasons behind these outcomes. Enabled by these granular, actionable insights, organisations can take quick, confident, and precise action designed to deliver maximum outcomes – ultimately helping retain and grow customer share”.
“For example, by combining experience and operational data you can examine the types of product and service interactions that lead to promoters and detractors. This level of insight can help inform and guide investments and innovations.”
The different sources of customer data
The sources of data concerning customers and their behaviour are varied and plentiful. Each data source offers a particular range of potential insights or benefits as well as limitations. The following list is by no means exhaustive or conclusive, but provides a high level overview of the main sources of customer data available to most companies.
- Customer satisfaction and feedback surveys: Feedback from surveys provide insights into customer perceptions and attitudes towards the brand as well as its products and services. Metrics like NPS (Net-Promoter-Score) and CSAT (Customer Satisfaction) are applied to the surveys to measure how well the brand is performing and identify areas the customer experience can be made more seamless. These surveys typically form the basis of a brand’s VoC (Voice of Customer) program. There are a number of limitations to using surveys, however as Libby Dale, CEO for SmartMeasures explains, “NPS and CSAT only provide a picture of what’s happening with people who have completed a survey. But most customers don’t provide feedback. Most customers who are frustrated with an experience do not complain. They just leave and tell others about their experience.”
“Surveys typically, only cover a small percentage of a company’s customer base. The opinions and perceptions of most customers are not explored or considered.”
2. ERP, CRM and other transactional systems: These are the database systems that companies use to manage and track the transactions they have with their customers as well as manage the performance and various functions of the business. They store all sorts of customer data, depending on the nature of the business including what customers have bought, how much they bought, how long they have been customers, their addresses, phone number and emails and so on. This data can provide substantial transactional, behavioural and historical insights.
The ability to offer hyper-personalised customer experiences depends on utilising this data to identify individual customer preferences and tailor the customer experience to each individual customer.
3. Marketing automation and analytics: The metrics provided by these systems measure and analyse the level of engagement customers have with the messaging and content an organisation is producing. They allow you to track website visits, online purchases and lead generation, identifying which advertising or marketing campaigns are successful and how to optimise them.
4. Social media: Social media can be a goldmine for real-time costumer insights and for monitoring the brand’s reputation. You can track what customers and detractors say about your organisations, including things they wouldn’t necessarily say in a survey response.
Combining these different data sources should provide a more complete picture of a company’s customers and their behaviour. Most companies have the capability and capacity to collect the necessary data, where they struggle is in their ability to consolidate the different sets of data and generate insights they can act on.
The different data sources the organisation maintains reflect the different tools used by different teams within the organisation. So, integrating these different data sources will typically involve integration between these different teams as well integrating the different tools they use. This is where the hurdles to customer data integration start to multiply and vary greatly for each organisation.
As companies grow and evolve the range of tools to manage the various aspects of the business, including all customer facing operations, begin to grow and become more complex. The ability to move forward may entail a complete revision of your marketing technology stack or deployment of a CDP (Customer Data Platform).
What should be integrated
What data you integrate and how – depends on what facets of the business and the customer experience you want insights on. An important step in combining different sources of data, according to Lisa Khatri, is identifying the right insights to use, and which to remove. This requires a mix of data-driven and business acumen-driven approaches.
She advises, “Taking an analytics approach prevents cognitive biases from entering the insights being generated. This is particularly useful when measuring what attributes have the greatest impact on your customer experience. Similarly, it helps keep you focused on high value programs, and ensures each data set is statistically significant to the other”.
“Importantly, when analysing experience and operational data together, don’t discount what you already know. When measuring the customer experience, including operational data elements that are similar to your experience data – such as online sales, web traffic, and number of products – is important when measuring your digital experience”.
Finally, Khatric identifies six key things successful organisations do when combining the power of experience and operational data:
- Treat experience data as a corporate asset – Considering the growing importance of experience, organisations need to establish enterprise capabilities to standardise, share, and control insights
- Modernise systems – By modernising systems and the approach to data collection organisations will capture the insights they need to make an impact
- Look beyond survey data – Experience data increasingly comes from a variety of sources, meaning listening platforms enabling conversational and text analytics are a must
- Carefully select the right operational data – Selecting the right data sets helps businesses and governments articulate value to executives
- Design for action – True value comes from the actions organisations take based on the insights generated from data. Leaders should continually be asking ‘What have you learned?’ and ‘What improvements are you making?’
- Tailor insights for different audiences – Designing the timing and content of alerts and reports to support specific decisions help existing operational processes.