According to the 2014 Communications Market Report from UK regulator Ofcom, the number of people with mobile connections in the UK reached 55 million at the end of 2013, up 6.5 million from the previous year. In fact, according to the report, Britons now spend more time on their smart devices than they do sleeping.
With all this activity running across their pipelines, surely operators have entered a new golden era?
The big data challenge
Despite first impressions, things are a bit more complex than that. Behind the rosy picture, the massive growth in data consumption is hurting operators' traditional text and voice revenues. Compounding this issue is the fact operators are still finding their feet in terms of designing profitable pricing structures; the data boom happened so quickly that many operators rushed out "all-you-can-eat" data packages to market in order to get a leg up on the competition. However, this resulted in price wars and eroding profits across the industry. The cracks are now clear to see; in 2013, total telecom services revenues fell by £0.6 million (US$0.95 million) to £38.6 billion ($61.2 billion).
As prices continue to be driven down, operators need to find new ways to make the data boom work for them. They are now looking at how they can use their unique position as data highways to turn this data traffic to their advantage and become data-driven enterprises. The most valuable subscriber data insights often only have a shelf-life of seconds, rather than minutes or days. Therefore, the ability to analyze and extract insights in real-time is critical. If operators are able to do so, they can then identify new upsell and cross-sell opportunities, build more accurate and profitable pricing plans and market to customers more accurately for greater ROI.
The upsell hurdle
Analyzing subscriber data in real-time can also help operators to quickly identify and segment customers based on their location, how profitable they are, which devices they use, and even the services they consume the most. Using this information, CSPs can start to identify customers and offer them upgrades based on the specific services they consume. As a result, operators can increase conversion rates, while also delivering greater value to customers.
For example, if an operator was launching a new mobile video streaming service, it could accelerate adoption by specifically targeting customers with compatible devices. They can then correlate this information with usage preferences to identify users who regularly consume that type of content. By identifying the most likely targets, CSPs can dramatically increase conversion rates and deliver greater value to their customers.
Conquering the data high jump
Ofcom's report also suggests that almost three in five adults used data services on mobile phones at the start of this year. A large portion of this usage is likely to be attributed to data-intensive OTT services, such as Netflix. With consumption only likely to increase and generate even heavier volumes of network traffic in the future, operators need to have a clear picture of traffic flows and associated costs in order to price their tariffs correctly.
Understanding how data services are being used is a key facet to solving this issue, providing the insights that operators need in order to introduce more profitable tiered pricing plans. By using big data analytics, operators can segment their subscribers on a more granular level and create pricing plans that ensure tariffs are aligned according to usage patterns, without the risk of cannibalizing their existing services.
For example, if someone has a 4G-enabled phone but is currently on a 3G network, they might be keen to upgrade to a 4G plan. On the other hand, if someone is a heavy data user, or a less profitable customer, the operator can offer flexible rates that move them onto a network connection that is more in line with their price tariff. For subscribers on prepaid plans, operators can analyze and assess usage to create tailored packages to encourage them to adopt postpaid contracts.
Conventional advertising and marketing campaigns are often something of a gamble. While marketers will have researched and analyzed target audiences, they can never be fully certain of a campaign's success until it has run its course. In this situation, having the right big data analytics capabilities can help operators monitor audience reactions to campaigns in near real-time, meaning that marketers can tweak and improve them while they are still running. Even before launching a campaign, analytics can be used to segment and profile subscribers. This can allow marketers to more accurately provide them with content that's of personal interest to them, as opposed to random promotional alerts that are immediately deleted.
For example, if an operator knows it has a high concentration of iPhone users in a particular area who regularly use Netflix, it could create an advert to target this niche audience. This could perhaps be an advert at a subway station, with an offer for iPhone users to gain improved video connectivity using Netflix. Essentially, by knowing more about their customers, operators can create personalised services, ensuring that the right messages reach the right people, at the right time and in the right context -- the holy grail of marketing.
Going for gold
Operators now have a golden opportunity to provide a new generation of data-driven products that offer greater ROI and improved service for customers. However, to fully take advantage of this opportunity and solve their revenue challenges, they must act now by changing the way they interact with their data. The right approach to big data analytics can help operators better understand their subscribers. This, in turn, will enable them to create services that are not just profitable and popular but also specifically tailored to each individual.
It is this key factor that will make is possible for operators to win this race and capture the gold.
— Rob Chimsky, VP of Insights, Guavus Inc.