How big data ensures seamless customer experience across channels?

With the prudent adoption of big data analytics to personalize experiences, 53% of the consumers are purchasing more from brands who personalize their shopping experience across all channels, according to MyBuy’s Personalisation Consumer Survey. If organizations want their customers to stay loyal, they will have to invest in the experience. With the view to achieving this, more than 50% of organizations will redirect their investments to customer experience innovations by 2018 as per Gartner predictions. This will lead to 40% more revenue per person.

When consumers visit the company websites, social media pages, and catalogs, while switching between multiple devices, big data plays a pivotal role to predict their behavior and create a seamless marketing and buying process.

According to a report by Oracle, the benefits of brands evolving to data-driven customer experiences are extensive (See Figure 1). Big data has ensured a significant shift in elevating customer experiences. The results of the survey have indicated the positive scenarios for the organizations as mentioned in the figure below:

Data-driven-customer-experience

Big data enhancing all customer channels

As the telecom industry is witnessing an explosion of competition, the most immediate impact has been an increase in customer churn. However, big data has proved to be the differentiating factor for delivering services across all channels.

Big data has helped the telecom operators to optimise their websites in such a way that it has helped to solve customer’s problems and convinced customers to buy from them.

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Having a seamless interface across all the channels was a challenge before. But now, big data has assisted the telecom operators in integrating their direct mail pieces to other channels. As these pieces are now integrated, customers see a very common interface which has lead an ideal experience for them.

Providing a customer-centric approach by integrating a personal touch is now catered by data analytics. Speech and text analytics is used to track customer interactions across all channels, including voice, social media, SMS, chat, email, and blogs. It has helped many brands to become more customer-centric by developing a sense of personal touch.

Unstructured data was always a challenge. Big data has now dug deep into the unstructured data mine and has led to some fantastic insights. Social listening tools are being used to learn what people are saying about the brand across the internet. Such unstructured data has helped to reveal a great deal about customer sentiments and has, in turn, helped the operators to tackle the addressable issues.

Using Big Data for Customer Experience Management

  • Validate and steer the marketing decisions

The data analytics solution provides information relevant for marketing, steering wise decisions regarding service packaging and marketing campaigns, resulting in increased operator revenues.

  • Optimize the network investment

Big data analytics have helped telecom operators to know customer behavior and customer-related issues to plan the network investments efficiently. This, in turn, has enabled them to avoid outages in the highest revenue areas and eliminate over-investment in lower priority areas.

  • Comprehensive visualization

Along with the flexible dashboards, big data analytics solutions provide many specialized dashboards supporting most essential use cases, like roaming monitoring, and VIP monitoring tailored for the customers.

Telecom operators are using big data solutions to review metrics in real-time to come up with the price for a product offering. After testing the price with different segments of customers in different regions, operators are coming up with the most optimised price. This is a win-win for the operators and the customers as customers get the price they are happy with, and the telecom receives a steady revenue stream with low customer churn.

Why data-driven customer experience makes the difference?

In the past, data concerning client interactions were primarily based on observation and person-to-person communication, but now, because of the thousands of data points that companies can examine about each customer, it can use trends that might otherwise go unnoticed to better understand and segment their customer base.

Pattern Analysis: Big data helps to determine customer behavior pattern based on either structured data like sequential demographic data or unstructured data like tweets about products.

Sentiment Analysis: This is helping the operators to know what customers are saying about their products/service and aids help them to address issues before they spread too big.

Recommendation Analysis: Big data plays a pivotal role to help give the best recommendation to the telecom customers to increase the conversion rate.

Marketing analysis: It helps the telecom operators to analyze customer interactions and optimise marketing decisions and messages.

With the programmatic advertising and email marketing metrics, operators are moving towards continual improvement cycling in their marketing program. Collecting the vital data has enabled them to analyze and improve their efforts to deliver a best-of-class customer experience.

Customer experience management becomes easy through big data analytics solutions as it provides compelling visualizations, graphs, charts and dashboard reports that allow businesses to understand and gain insights on their survey responses at a glance!

 

Future of CEM with Big Data Analytics

The global big data revenue is expected to reach $203 billion by 2020, meaning that operators need to move ahead of customer service performance and quality and focus on customer perceptions to become a significant part of this revenue growth. For example, the data analytics tool can enable businesses to compensate the customers for bad experiences before they even complain, possibly turning a potential red flag into a wow moment.

A leading telecoms operator developed a mobile app to display the status of a customer’s inquiry which in-turn reduced the inbound calls. Such should be the application of big data analytics solutions where an offer or service is highly customised. It can help the customers to see their CLV-based status, the expected service level, and features or services they might have to pay for.

In the years to come, ‘Crystal Ball Analysis’ will be the widely applied in customer experience management, meaning that, analytics will be beneficial to target people depending on their mood, in happy or dejected moods, based on what they are typing or looking for.

Another significant use case of big data will be for people working in sales and marketing in telecom. They can use analytics to forecast the impact of their actions and provide more personalized pitches or content to individual customers, instead of depending on historical data.

‘Predictions-as-a-service’ will see growth, wherein big data analytics will be used to gather the data from various platforms and analyze how it is performing against broader regional and global sales trends in the telecom sector. This will be backed-up by understanding the influences of current events, economic factors and even the weather on its sales pipeline.

Conclusion

Big data has the potential to move the telecom strategy from segments to true personalization. Now, with big data, operators have unprecedented amounts of information, and through proper utilization, it has allowed them to determine customer needs before ever interacting with a customer.

Using big data analytics solutions, operators can analyze behavioral triggers, and tailor a personalized marketing effort to meet their client’s needs for relevant email marketing and programmatic advertising.

 

 

 

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