Customer Experience and AI: A Practical Guide for Data-Driven Decision Making

Customer Experience and AI: A Practical Guide for Data-Driven Decision Making

You know very well that you need to take into consideration your customer’s holistic experiences if you want to reach out and score sales with him or her. But how would you know about your customer’s needs if you don’t reach out to him prior to the sale proper? The simplest solution would be to gather data about your prospective customer.
This short article will give you information about data-driven decision making and its relation to augmented intelligence and customer experience.

Data-Driven Decision Making

The business world recognizes Data-Driven Decision Making (DDDM) as an approach that places emphasis on the importance of decisions backed up with credible and verifiable data.
This article opened by telling you that you need to learn about your customer first before you can sell him something of value to him. You can’t make a sale if your product or service isn’t aligned with his needs and preferences. This is precisely why gathering data for a DDDM approach is important.

Data Processing and Augmented Intelligence

Modern CRM programs like Salesforce are now graced with the powerful presence of augmented intelligence. This technology lets your salespersons enjoy a streamlined approach to data gathering, verifying, grouping, and analysis. AI also enables users to apply customer data during various decision-making points in the sales cycle.
Here is a sample situation to show DDDM, augmented intelligence, and human intellect working together to achieve a common goal.

  • A salesperson asks himself if he should continue with a product demonstration to a prospect who becomes reluctant to accept his offer.
  • Data he collected from personally interacting with this prospect could be quickly reviewed from the AI-driven CRM tool to look for behaviors or factors that might have affected his change of sales thought.
  • He finds out that the customer became reluctant because of a lacking description for the product’s use. Previous data showed the customer’s buying behaviors is anchored at scrutinizing the product descriptions first before proceeding to buying it.
  • The salesperson decides on the matter and takes appropriate steps guided by his own insight, his desired customer experience levels, and the customer data he retrieved from the CRM tool.
  • He sets out to fill in the gaps about the product’s description so that his reluctant customer may understand the totality of the product offered to him. This way, he won back the customer’s trust and made his prospective customer an actual one.

Had the salesperson not looked up to customer data in the AI-driven CRM tools, he might not have learned about the source of the prospect’s reluctance to buy, and might have missed a chance of making a successful sale just because of it; not to mention that the customer will also have a negative customer experience with the brand.

Working Together Towards Better Sales and Better Customer Experiences

To sum it up, data-driven decision making stems from a salesperson’s use of his own insights and inputs from augmented intelligence tools like Salesforce. When DDDM, AI, and the salesperson’s own efforts combine together, the result is a productivity increase on the business side and a higher customer experience satisfaction on the customer’s side.

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