The digital age has not only changed the way a company is managed, but it has changed potential customers, so when several of the large companies agree to invest their efforts in the same area, it can only mean one thing, that this is a profitable investment.

Organizations that dedicate their efforts to leverage customer behavioral data to generate behavioral ideas outperform those that don’t by 85% relative to sales growth and more than 25% in gross margin.

In a digital world where customer focus, personalization and customer experience separate successful companies from non-successful companies, it’s no coincidence that these companies thrive at high speed. However, the number of organizations that only take advantage of a mere fraction of the behavioral data at their fingertips is surprising.

Data enables digital customer customization

Companies like Netflix, Amazon, and Google know that the key to understanding their customers lies in quantitative information revealed through their behaviors, which give a much more accurate picture of what their customers want and need.

For example, 75% Netflix viewer activity is driven by recommendation. In the case of Amazon, 35% of its sales are generated through its recommendation engine.

However, personalization is just a case-in-case (incredibly lucrative) use of how these digital-age titans are using customer data and behavioral analysis.

What about privacy?

To provide the experiences customers expect and demonstrate a 360-degree understanding of each customer, businesses need a new generation of technology as well as a lot of data.

However, as recent incidents have been laid bare, not all companies are gaining the trust of their customers to do the right thing with these technologies and data.

The 72% of customers say they are more afraid that their data will be compromised now than they were two years ago, and nearly half of customers (45%) are confused about how companies use their data.

Faced with this situation, companies face a paradox: how can they provide personalized experiences when customers don’t trust them? The answer lies in transparency, when customers understand the benefits of using their data, they usually agree to provide it.

Building trust and balancing personalization with privacy will be key for companies to meet customer expectations in the Fourth Industrial Revolution.

A bad experience can be an abandonment

Today, leading companies are increasingly focused on the entire customer journey. They are using data to understand and segment customers based on their behavior, looking for ways to improve the customer experience and deliver real business value.

67% of the customers say that bad experiences are grounds for abandonment, however, only 1 in 26 dissatisfied customers complain. That’s why companies can’t rely on their customers to trigger a red flag to accurately assess consumer experience, satisfaction, or predict abandonment and retention.

However, warning signs can often be detected through a customer’s behavior and, with appropriate analysis, ensure that signs of problems are detected on their radar early, so that there is still time to act.

Not receiving enough value from a product or service can be another major cause of rotation that customers often don’t complain about and are difficult to detect, without customer behavior analysis and segmentation.

As discussed above, Netflix is a clear example of how to deliver a good digital customer satisfaction strategy, in this case by leveraging analytics and customer behavior data, Netflix is able to identify the amount usage activity that an individual customer needs each month to receive sufficient value and keep their subscription active. If a customer’s monthly content consumption falls below that threshold, the probability of abandonment is triggered.

As a result of these efforts, Netflix has significantly reduced its churn rate to a substantially lower point than many of its major competitors. In addition to increasing the lifetime value of its customers, this also allows the company to spend more on customer acquisition.

On the other hand, for new product suggestions, Amazon’s recommendation algorithm (responsible for boosting 35% of its revenue) uses customer behavior data such as:

  • A user’s purchase history
  • Items in your shopping cart.
  • Articles you have rated and liked
  • What other customers have seen and bought

Segmentation an indispensable point

However, in order to meet the goals of customer customization, it is important to perform a good pre-segmentation, and identify which customers may be interested in each company’s products.

Source: Vector from own data
Source: Vector from own data

Each customer is different, has their own needs and it is convenient to communicate with them in a unique way. That’s why the key is targeting and activating custom campaigns that allow companies to launch concrete actions.

The Flormar cosmetic brand is an example of how to carry out this type of strategy. The company has invested much of its efforts in the omnichannel data acquisition phase, which has led it to improve the recruitment of customers in both physical stores and the online store in addition to designing personalized campaigns that generate sales Incremental.

In general digital clients or also known as 2.0 clients have a number of common patterns:

  • They are very knowledgeable: this information is not only limited to the qualities of the product, but also to factors such as the price or quality of customer service, and this will require additional effort on the part of the company.
  • They are smarter: the digital customer is more immune to traditional advertising and can evaluate the authentic quality of the products.
  • They’re more impatient: the abundance of outlets and products means that if a company doesn’t quickly meet its needs, customers look for other options. Therefore, it is important to take care of the usability factors that make the purchasing process a quick and simple experience.
  • Share your experiences: Massive tools, such as social media, have made it possible for both a good and bad shopping experience to go viral and reach thousands of people.
  • They are demanding: The digital customer knows their value and this means greater demand in both the quality and price of products and services.
  • They’re changing: Customers 2.0 are always experimenting and it’s not easy to build loyalty.

Conclusions

Digital customers, like non-digital customers, are complex, providing an additional effort for companies to keep the business booming. Working with as much information as possible, from data sources that show user behavior, should be a critical part of the CX strategy.

The storage and management of customer-related data 2.0 from a wide range of sources is essential to be able to have a better perspective.

On the other hand, in an era of large volumes of data, hyper-connected digital customers, and hyper-personalization, segmentation is the cornerstone of consumer understanding in the modern digital business. Along with personalization of campaigns will be two of the most important strategies to improve the customer experience and thus increase loyalty and reduce abandonment.