Delivering an exemplary customer experience is a huge benefit for all businesses
The better experiences customers obtain, the more positive the reviews and thus revenue growth
It also helps in reducing complaints and other frictional issues
Data-driven analytics nurtures deep connections between the business and its customers, allowing them to create more dynamic, responsive, and personalized services and customer journeys.
Let's examine how:
Personalization: The company can craft an entire customer touchpoint based on personalization and deliver relevant content at an apparent time. The data set shared with marketers can be used reliably and accurately to assess customer needs, better identify consumer profiles and enhance programmatic advertising that will expose them to the products or services that will interest them most. That includes call-to-action, content offers, and e-mails.
Countless variables: An endless stream of data presents infinite opportunities to select the best way to refine marketing efforts. Data can uncover patterns and trends used to research interpretation, design surveys and studies, boost ROI, and reduce the cost of acquisition per customer.
Create frictionless experiences - Customers' bargaining power is usually high after comparing the features and benefits with their needs. There is potential for the customer to switch to the competition when they want to spend less time shopping on websites that poorly recognize their previous information. If the business can respond to a customer’s needs with agility, it improves the customers' experience and it is more likely that they will return later on.
Applying data to deliver sophisticated Customer Experience
A data-driven customer experience is crafted by collecting data from every customer touchpoint.
Here are 10 tips to consider before organizing the data structure:
1. Draw the right data
Effective communication is built on the relevance of the data collected and attaching it to customer behaviours whilst prioritizing it. The focus should be kept on what the company wants to achieve and draw insights from every customer touchpoint to understand the behavioural patterns. Once enough data is gathered, the system can discover statistically compelling interactions with the company and customer, providing avenues to drive growth.
2. Take a comprehensive approach to analyze data
Data is raw, free-flowing, holding numbers in their native format until it's needed. It can be queried for related information, creating a large set of data that can be enough to analyze and answer business questions. However, examing the life cycle of one’s data is necessary to derive the correct conclusion. There is a liability in making decisions based on false trends or on biases, as is the case when the data hold counterproductive information.
3. Agile and adaptable
Customers and trends are evolving prompting businesses to be agile. If change is not fast-tracked, it will result in lost customers, losing out to competition and thus decreased market share. An organization's agility increases through continuous interaction with the consumer and demonstrating responsiveness.
4. Anticipate customer needs and requirement
Instead of finding out what the customer wants, structured data predicts future trends by collecting information from the business environment. The business can draw curved lines with sufficient data and begin to predict customer behaviour
5. Expose brand content to where consumer located
Brand penetration is extremely important, and structured data helps in guiding product placement so the brand’s identity is in prominent locations in the marketplace. The more customers see it, the more they recognize the product and identify it on social media platforms and online platforms helping grow sales.
6. Communicate with the unique selling points
By clearly articulating the unique selling point (USP), organisations can help customers distinguish and identify them, thus gaining a competitive advantage. With the volumes of data available, it is possible to highlight the USPs of their product to target customers and market suitably.
7. Plan the buyer's journey
The organisation can map their buyer's journey for each buyer personas with extensive data management. This not only allows them to refine the customer experience at every stage but allow for opportunities to connect with them.
8. Don't compromise quality
The quality of data to refine customer experience should never be compromised. Nevertheless, data acquisition methods should not degrade that experience. Don't force customers into data collection processes, thus inconveniencing them. Be careful of when, and how many times, you are requesting feedback to ensure you are not gathering repetitive information.
9. Use every platform
Collect data from customers irrespective of what platform they use, whether on a computer or smartphone. Their behaviour may vary between platforms, and getting feedback allows you to further refine the consumer experience.
10. Clarify the strategies
Businesses and CX leaders must analyse data frequently and not just make note of the feedback being given, or the variation in responses in the data sets, they must also constantly refine their marketing strategy based on the results. Good data analysis can benefit the company by adapting swiftly to customers changing behaviours and attitudes.
Consumer trends are shifting continually and businesses must adapt to the changing needs post-pandemic. This allows you to improve not only the customer experience but also build customer loyalty. Creating a better customer experience positions your organization to be innovative, intelligent, and better suited to survive in a fast-changing environment.
How can customer data and insights lead organisations towards customer-centricity? Read on
