Linus Gregoriadis
Linus Gregoriadis 11 February 2019

Building the right company culture for customer analytics success

The ability to take an integrated approach to customer data is very much dependent on the culture within the organisation, according to a new report from Digital Doughnut sister company London Research. While technology plays a crucial role in enabling organisations to be more customer-centric, companies must ensure they have employees with the right skill sets to get the most from their investment.

Customer Analytics: The 20 Attributes that Lead to Business Success — produced in partnership with Adobe — has found that only a minority (44%) of companies surveyed say they already have a data-driven culture in place to drive their customer intelligence activities.

The research identifies a group of customer intelligence ‘leaders’, made up of companies whose capabilities are classified either as ‘established’ or ‘advanced’.  

Culture-related organisational capabilities relating to data and insights are much closely associated with leaders than with laggards. Below we outline the five most important attributes highlighted in the report that relate directly or indirectly to culture.

#1. A data-driven culture

Customer analytics leaders are more than twice as likely as laggards to have a data-driven culture that helps to drive their customer intelligence activities.  

Companies must embrace clear processes for decision-making based on the insights that emanate from the data if they want the right type of culture to take hold.

Because organisations will ultimately get the type of behaviour they measure, employees need to be rewarded for achieving data-centric goals based on key performance indicators that show improvements in customer experience and commercial importance.

With customers being able to interact with a business in multiple ways, different data on that customer may be held by different teams across the organisation. Companies that can synthesise this data, draw actionable insights from it, and share these throughout the business, will be the most successful.

#2. Democratisation of analytics

As already touched on above, it is important that companies don’t restrict access to data and insights to analytics teams and data scientists if they are striving to achieve a competitive advantage through their use of data.

‘Data democratisation’ involves the use of analytics tools that can be shared with and understood by those who aren’t necessarily specialists in analysing and manipulating data.

The ability to take this joined-up approach to data is dependent on the culture of the organisation, and whether there is a healthy environment for collaboration, sharing, and for new ideas to take hold.

Businesses should establish a way for insights from different departments to be shared throughout the organisation in a format that is easy to digest.

Customer analytics leaders are also more than twice as likely as laggards to say that analytics have been democratised within their organisations. 

#3. People to align analytics with strategic and commercial goals

Customer analytics leaders are almost twice as likely as laggards to have managers who can bridge the gap between analytics and the over-arching commercial objectives of the business.

Agile businesses can improve business performance by employing the right kind of people to close the chasm that sometimes exists between specialist analytics teams and the rest of the business.

Though the ‘operationalisation’ of insights becomes significantly easier when you have the right analytics software in place, it also requires managers that can help to surface the right data, and also to translate insights into actions that benefit the business commercially.  

Less than half of companies surveyed (45%) have managers who can bridge the gap between analytics and strategic commercial goals, an important requirement often overlooked by organisations that struggle to translate data into commercial uplift. Leaders are 92% more likely than their peers to say they have the managers in place to do this. 

#4. A strategy and roadmap for capabilities development

Customer analytics leaders are 106% more likely to have a customer intelligence strategy and roadmap for capabilities development.

Although agile organisations can benefit from a culture that encourages ad hoc tests and experiments, tactics and ideas for optimisation should be happening within a broader strategic framework that systematically helps the business to meet and anticipate customer needs.

As the marketing team should act as a customer champion, it makes sense for the CMO or head of marketing to be responsible for the customer intelligence strategy. But if CMOs are to take responsibility for customer intelligence strategy, it is essential that they co-operate with other teams in the business to ensure that all efforts align with the customer intelligence strategy.  

#5 Buy-in from the top of the organisation

Customer analytics leaders are 59% more likely than laggards to have buy-in from the top of the organisation for digitally-driven customer intelligence. 

A successful customer analytics strategy requires the right kind of technology and people to make it work. This, in turn, requires senior managers within the organisation to understand the importance of customer analytics, and to authorise the appropriate level of investment to support business goals.

While some companies may thrive with a bottom-up approach, a holistic customer analytics strategy is contingent on the backing from C-suite stakeholders such as the CMO, CIO, CDO, and even the CFO.   

Download Customer Analytics: The 20 Attributes that Lead to Business Success from Adobe to learn more (registration required). 

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