Here we are with another part of the series “B2B Analytics and its Scope in Industry”. This time we are representing Telecommunication Industry. Telecommunication is the transmission of signs, signals, messages, words, writings, images and sounds or information of any nature by wire, radio, optical or other electromagnetic systems. Telecommunication occurred when the exchange of information between communication participants includes the use of technology. It is transmitted either electrically over physical media, such as cables, or via electromagnetic radiation.
Early means of communicating over a distance included visual signals, such as beacons, smoke signals, semaphore telegraphs, signal flags, and optical heliographs. But now the technology has been changed in this 21st century. Now for long-distance communication Telecommunication Industry developed various technologies such as electrical and electromagnetic technologies, such as telegraph, telephone, and teleprinter, networks, radio, microwave transmission, fiber optics, and communications satellites. Let us discuss it in brief and understand the use of B2B Analytics and how analytics is impacting on the Telecommunication Industry.
Telecommunication Industry Overview:
- Wireless Telecommunication Carriers: 256 billion USD
- Annual Growth: 4.6%
- Broadband Carriers: 73 billion USD
- Network Equipment/ Infrastructure Companies: 27 billion USD
- Annual Growth: -3.8%
- Companies: IQR Consulting, Teradata, Guavus, InfoFacees, Datameer
Telecommunication Industry Analysis:
Network analytics services can be an important tool for communications service providers (CSPs) as they work to deal with the global marketplace dynamic of convergence, in which digital networks and other technology developments are accelerating the blurring of industry lines and expanding the ranks of their competitors. The resulting challenges include increasing data traffic, decreasing revenue per user and users growing expectations for service quality. In the new world of convergence, major investments will be required, both to introduce the enabling technologies needed to manage network expansion and control, and to improve CSPs capabilities to appropriately manage service quality.
Network analytics for CSPs can provide invaluable assistance in effectively targeting both types of investment—helping CSPs be more intelligent about where they spend their money, while at the same time, prioritizing service quality issues that may need to be addressed.
Customer Analytics of Telecommunication Industry:
Customer Insight for Communication Service Providers is an advanced application that converts unfiltered network data into defined and usable customer data. The refined data helps accelerate returns with unique and customer-specific use cases for NPS & churn, customer profiling and customer engagement.
- Minimize subscriber Churn: Combines customer behaviour and experience analytics with the targeting of subscribers based on propensity to churn score. Uses Churn Propensity, Predicted Churn Date and Keep Score.
- Improve Customer Satisfaction: Correlates Net Promoter Score (NPS) with customer behaviour and experience data. Identifies drivers of promoters and detractors, and allows analysis of individual factors.
- Increase Marketing Revenue: Identifies meaningful customer segmentation based on customer activity, customer behaviour and time spent with weighted interest scores, recency and frequency.
Marketing Analytics of Telecommunication Industry:
The first step in creating a marketing analytics engine is to identify and integrate multiple data sources, including information about customers, products, online activity, sales and campaign results, and contract lifecycle status. The next step is to integrate third-party data, such as Dun & Bradstreet information. A solid marketing analytics engine can incorporate several hundred variables that describe your SMB customers, enabling you to build very effective profiles of them. Within a few months, a service provider can integrate a wide range of data sources into an aggregate view to look at customers in totality.
With this data foundation, marketers can not only see a customer’s products, services and transaction history but understand that information in context with purchased third-party data – information such as the business size, vertical market, various firmographics and more. Once you start to organize the data, questions or gaps will appear, and you will begin to understand what additional data you can get. You can continue to add more data sources as you find them, or as your organization merges with or acquires other entities, to continue to nurture a more comprehensive view of customers.
Analytics-driven marketing raises the standard, moving away from mass marketing products a provider believes it can sell, and toward targeted campaigns based on a personal understanding of subscribers’ unique wants and needs. Building on the data foundation, analytical models can provide rich insight into your business and your customers to guide you to the right prospects to target and the right offers to make. With analytics, you can optimize price, customer segment and product mix. You can:
- Perform complex calculations of individual customer bills under any number of price plans to generate a precise, prioritized list of offers that balance the needs of subscriber and provider.
- Analyze subscribers across psychographics, demographics, billing, utilization, customer lifetime value, products and services to gain new intelligence and context to define offers, promotions and pricing.
- Test what-if scenarios such as price changes or promotions and determine the likely effect of these factors on future demand.
- Assess all the revenues and cost to serve a customer over the expected duration of the relationship to make smarter decisions based on customer value, not just customer revenue.
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Outputs of the Marketing Analytics Engine in Telecommunication Industry:
The marketing analytics engine supplies a variety of outputs to telecommunication industry business users. For example:
- Multivariate segmentation identifies homogeneous groups of customers within the embedded base derived from statistical patterns.
- Profiles clarify the attributes and product needs of each set of customers. With the addition of third-party data, you can now assess customers uniqueness across many variables and generate a profile of the ideal candidate for a particular solution.
- Propensity models reveal the key drivers of potential marketing success and rank customer lists for specific campaign purposes.
- Micro-segmentation further homes in on target customers and helps clarify how their attributes could translate into marketing action.
- Automated campaign management enables campaigns to be created and executed against customer lists in a fraction of the time of traditional methods.
- Ad hoc query capabilities enable business users to explore the data to test theories and ask what-if questions.
- Interactive dashboards show how effective a campaign has been, how the marketing analytics engine increased campaign take rate, and which factors influenced success.
Sales Analytics of Telecommunication Industry:
Predictive analytics and data mining solutions are designed to help sales and marketing professionals in the telecommunications industry discover data-driven patterns, customer segments and relationships in their data that impact their activations, ARPU and other key performance indicators (KPIs). Predictive analytics can help telcos predict the impact of their marketing and sales strategies— from store location to handset promotion, to customer segmentation, to offer bundling, and act on customer insights.Telcos are able to create and operationalize predictive rules that deliver continuous improvements in sales and marketing performance.
Available either as fully managed and hosted analytical services or licensed software, analytics solutions provide telecom sales and marketing professionals with:
- Segmentation of consumer profiles
- Segmentation of B2B market segments
- Predictive lists providing prioritized targeting of B2B and consumer segments
- Predictive response providing detailed profiles and drivers of cross-sell, upsell and offers
- Pricing optimization providing analysis of the cause and effect impacts of changes in pricing models and packages
- Risk-reward pricing
- Customer churn analysis and insights
- Inventory optimization providing analysis of marketing impacts on existing inventories
We discussed Telecommunication Industry, the eleventh part of the series “B2B Analytics & its Scope in Industry”. Previously we discussed nine industry in B2B Analytics were “Food-Chain Industry”; which was the first part, “Banking Industry”; the second part, “Healthcare Industry”; the third part, the fourth part was Manufacturing Industry’s a part-“Food Manufacturing Industry” and “Discrete Manufacturing Industry”; the fifth part. The sixth part we discussed the “Education Industry”; the seventh part was “Insurance Industry” and eighth part was “Government Data Analytics”; ninth part was “Retail Industry” and the tenth part was “Transport and Logistics Industry”.
In our next edition, some more interesting industries to be left for the discussion be ready to take a deep insight and we will discuss a lot about them. Stay tuned with us for further more deep insights in the industry. The next part will be out soon.
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