3 ways the role of data scientist benefits CX teams

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Customer experience should be teamwork. Companies that appoint an experience manager or customer manager get 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 IT, sales, marketing and service desk help.

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 role of data scientist can derive even more value from data. Data scientists don’t just use and maintain behavioral models of customers, they create new ones from scratch. And they don’t just analyze and report key metrics in models, they discover new ones. Ultimately, a person in a data scientist role can better understand the mathematics and methodology of business analysis software.

Here are three strengths that the role of data scientist brings to a CX team in addition to a data analyst or a standardized analysis software package.

1. Discover new factors and influences

The factors that move a non-customer up the ladder to 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 toolkit.

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 tap into a new demographic, a new product or service that attracts a potential new customer base, or when the company brings its offerings to a new vertical, new models are a necessity – and data scientists can create. , test and implement these new models.

Data scientist demand graph

3. Outperforming standardized analyzes

Regression models for descriptive and predictive tasks and cluster analysis for studying populations can help CX teams get the most out of the data. But pre-programmed software only uses a handful of available math tools and techniques, which may not be the best solution 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 have a designated role – he can participate in CX projects as needed.

Organizations may also consider hiring a data scientist consultant if none are available in-house and hiring a consultant is out of budget. However, this advisory relationship should be long term: if the team is going to use this resource regularly, it pays to stay with someone who knows the company and its customers.

Dig deeper into AI for sales

Sean N. Ayres