Using specific language increases customer spending

Speaking to customers in concrete, specific language makes them feel more cared for and important

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Use concrete, specific language when interacting with customers to increase satisfaction and spending

Impacted metrics: Customer satisfaction | Customer spending
Channels: Sales team | Customer service | Retail store

Recommendation

Train your team to use specific, concrete language when interacting with customers: “Let me check how much it will cost to upgrade your subscription” not “Let me look into your query”. Or “I’ll look for that t-shirt in grey” not “I’ll look for that”.

Effects

  • Increased customer satisfaction and customer spending (9% and 13% respectively, for the firms in this study).

  • The effect was tested and holds in different situations: in speaking or in writing, searching for a product or trying to solve a problem, and across different firms and product types.

  • Works in all forms of interaction (e.g. live chat, face-to-face), when selling to or supporting a customer, and across different firms and products.

Why it works

  • Using concrete language suggests that the employee paid attention and listened to the customer, making the customer feel unique and important.

Limitations

  • The effects work during an interaction between you and the client, they don’t apply in one-way communications (e.g. website, email campaigns).

Companies using this

  • At the moment, companies don’t appear to be training their employees to use concrete language in customer interactions.

Study type

Market observations and Lab experiments, United States and Canada.

Source

Packard, G., & Berger, J. (July 2020). How Concrete Language Shapes Customer Satisfaction. Journal of Consumer Research.

[Link to research paper]

Affiliations

Schulich School of Business, York University and The Wharton School, University of Pennsylvania.

Remember: Because of the groundbreaking nature of this paper, it could be disproven in the future (although this is rare). It also may not be generalizable to your situation. If it’s a risky change, always test it on a small scale before rolling it out widely.


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