3 Ways the Data Scientist Role Benefits CX Teams

Customer experience should be a team effort. Companies that appoint a Chief Experience Officer or Chief Customer Officer are off to a good start, but a larger team is more beneficial and may include a CX manager; an application manager; analysts; a data scientist; and help from IT, sales, marketing and the service desk.

CX analysts cover a range of data processing tasks and are necessary for a well-designed CX team. Analysts collect and cleanse data from client applications; monitor social media; and evaluate survey data for customer profile data, behavioral information, and metadata to refine CRM systems.

But including a data scientist role can extract even more value from data. Data scientists don’t just use and maintain patterns of customer behavior, they create new ones from scratch. And they don’t just analyze and report on key model metrics, they discover new ones. Ultimately, someone in a data scientist position can better understand the mathematics and methodology of business analytics software.

Here are three assets that the role of data scientist brings to a CX team in addition to a canned data analyst or analytics package.

1. Discover new factors and influences

The factors that move a non-customer up the ladder to become a loyal customer are well understood – teams are already paying attention to these metrics. But there are still unknown influences that attract customers.

Data scientists can research data to discover new products and services that customers are looking for and add them to the CX team’s toolbox.

2. Build new behavioral models

Customer behavior provides valuable data to adjust models that help sales and marketing teams determine next steps. But when companies are tapping into a new demographic, a new product or service that appeals to a new potential customer base, or when the company is offering its offerings in a new vertical, new models are a must – and data scientists can create , test and implement these new models.

3. More powerful predefined scans

Regression models for descriptive and predictive tasks and cluster analysis for studying populations can help CX teams get the most out of data. But off-the-shelf software only uses a handful of available mathematical tools and techniques, which may not be the best fit for a particular situation. Data scientists can select the best method for the specific needs of a CX team.

The CX Data Scientist does not need to be a designated role – they can participate in CX projects as needed.

Organizations may also consider hiring a data science consultant if one is not available in-house and hiring a consultant is not budgeted for. However, this advisory relationship needs to be long-term: if the team uses this resource regularly, it pays to stick with someone who knows the business and its customers.

Sean N. Ayres