Mobile Business Shock: Device-Driven Research Spots Revenue-Impacting Trends

Ever since the smartphone appeared, mobile operators have been driving blind.  Blind, because they lack vital intelligence on usage shifts from new apps and services that are deadly to revenue streams.

Perhaps the biggest threat that Over The Top (OTT) players and apps pose to telecoms is the unpredictability they bring to the network equation.  When Netflix videos rose out of nowhere to become the biggest bandwidth hog in North America, it hit the cable operators completely by surprise.  But were the Netflix spike detected sooner, cable operators could have course-corrected their business plans, operations, and pricing enough to meet the usage paradigm shift that Netflix set in motion.

In mobile too, apps have been known to devastate SMS revenue or cause similar earthquakes in mobile business models.  Yet another uncertainty factor is the effect of WiFi bypass, a huge path to the net that is simply not tracked by a cellular network’s CDRs.

Well, help is on the way from Mobidia, a small but innovative market research firm out of Vancouver who’s found a simple but powerful way to gather the kind of rich mobile usage intelligence that so many have been desperate for.

Here to explain his company’s unique research service -- and the mobile app that’s driving it -- is Chris Hill, Mobidia’s Vice President of Marketing.

	Dan Baker: Chris, please explain how you collect your mobility data?

Chris Hill: Dan, our data collection is done through a crowd sourcing app that runs on smart phones and tablets.  We give the app away for free on the iPhone and through GooglePlay.

People use the app to manage their phone bill and get bill shock alerts.  For instance, the subscriber may be travelling and consuming much more data that they thought, so they get hit with a big bill.

It’s a problem for the carriers too because of the support calls, having to go through revenue negotiation, and customer frustration.  The end user also suffers because they are saddled with a big bill and they feel they are being treated unfairly.

We send notices to our app user about their overages.  Along the way they get educated about their own usage patterns, so a byproduct of this is that many of the subscribers actually end up using more data because they feel more in control.

	Are operators getting better at managing the bill shock issue?

In the near term, I think the problem has become more acute because the data plans have become more complex.  Before, people were on mostly unlimited plans.  But most of the postpaid mobile world today is on some sort of metered (or tiered) plan.

This is why there are many “rabid fans” of our app.  Without some guidance on how much data is being consumer, it’s as if the user is taking a long trip in a car where fuel gauge is busted.  He doesn‘t know how far he can go.  He could end up walking home.  He can be very frustrating, and the experience is the same for users around the world.

And now mobile is moving into group and shared plan, so if you’re the guy paying the bill, you not only have to worry about your usage, but also that of your kids or employees.  So our app helps the users deal with these growing data usage and budgeting problems.

	And how do you turn your bill shock alert app into market research data?

Well, every one of the devices where the app lives becomes a probe -- or at least potentially.

It’s up to the users, but Mobidia requests that they allow us to collect data on their usage anonymously.  It’s purely optional on their part, but a high percentage of users agree to that as long as the information is kept anonymous.  Today Mobidia has millions of users worldwide providing daily reports on how they are using their smartphone.

Mobidia makes money by reselling our data.  Now it’s important to recognize this is not only about data usage.  We also connect data usage with the apps and services people are using.

	What sort of data do you collect and how unique is it?

We basically look at any network that is connected to the phone.  We track the traffic riding on the cellular carrier’s network but also the WiFi network.  Our data can track usage on the home carrier network, the roaming cellular network, and WiFi -- both public and private.  Mobidia also knows the specific cellular carrier of the phone.

It’s interesting because when we first looked at WiFi on cell phones, we were surprised that very few companies report this information.  Yet when you look at the usage, the WiFi component is often quite staggering.  In Europe, for example, WiFi is about 80% of the data begin consumed on a smartphone versus only 20% over the cellular network.  So you can start to see that if you’re missing 80% of the usage time, you are missing an opportunity to truly understand what the subscriber is doing.  This means that any telco network based analytics doesn‘t have visibility on the WiFi usage.

There are many pivot points in the data.  For instance there are time-of-day charts and the type of user being tracked.  Lots of subscriber plan information is also known.  For instance, Mobidia knows what carrier the user uses and what capacity plan: 300 Mbyte, 1 Gigabyte, or an unlimited plan.

You can get real specific and drill down to see how a user spent 100 Mbytes on Facebook when they were roaming in Mexico last week.  The data is driven from real users and real usage.

	Aren‘t there other sources for this research?  I see stories about the popularity of mobile apps in the press fairly often.

Yes, it’s true there are other sources.  The trouble is a lot of the information available is based on the number of app downloads -- that’s the sort of data you generally see reported in the press.

For instance, other analytics firms will track GooglePlay and iTunes, and from that you learn what the top apps downloaded are.

But downloads and usage are two different things.  For instance, the average SmartPhone user might have 30 to 50 apps on their phone, but they are only using 20 on a regular basis.  So that’s what makes Mobidia’s continuous tracking of app usage unique.

There are also some very large market research companies in the business such as Nielsen, Experian, and comScore.  Typically these players take a panel approach to the issue because they lack the interaction with users that we have.  So if a market research firm has 2,000 people on its user panel in the UK, compare that to the 70,000 people in our network there -- and it’s growing.

	What kinds of segmentations can an operator look at in your data?

We have data broken down by device and operating system, so you can segment by Samsung Nexus vs. an iPhone vs.  HTC users.  Another popular data pivot is smartphone vs. tablet.  Are people doing things differently on those types of platforms?  LTE is another popular data cut, and they want to know: what’s the difference between 3G vs.  LTE usage?

To gain publicity about our research service, we actually share some of our data in a quarterly white paper.  The subject of our most recently study compared LTE usage in U.S., Korea, and Japan.  It also looked at WiFi vs. cellular and the different apps.  One of the issues was around how much data was being used in different scenarios.

	Who’s buying your research and what do they find valuable in it?

Basically we sell our research to groups: telcos and mobile app vendors.

At telcos, the key parameter they look at is WiFi.  How much of a threat is it?  Is it an opportunity?  Is our offload strategy working?  If so, where is it working and how is it working?  And how are users utilizing WiFi?  For example, is it used to manage their overage or underage?  This information is key for folks who do mobile pricing strategy.

One customer of ours is a Tier 1 Group operator in Europe who owns a number of cellular properties.  We look at 18 of their networks, plus networks in Korea and the US as benchmarks.  And we generally give them a quarterly report on 20 to 30 KPIs around WiFi and cellular usage.

The other main research customer is the mobile app vendor.  Companies like Skype or Twitter are very interested in these statistics.  They use the data to benchmark their competitors.  So in a typical engagement, there’s a quarterly subscription looking at 35 competitors across 50 countries with penetration rates vs. the competitor.  Mobidia also provides average amount of time spent in the app vs. competitors.  And we also supply information on the average number of times those apps are being pulled up, viewed, and used.

	How much detail can you get on usage patterns?

In many cases, the data can get quite specific.  For instance, you can discover that the average user in Germany on a Vodafone network on the weekends consumes X amount of data via WiFi versus Y amount by EPlus, its competitor.

And because our data is all based on the device itself, we also track things like SIM swapping -- what are the behaviors of users who take the carrier’s SIM card out and put a competitor’s in?  And how is data being consumed on that other SIM?  Similarly we also have information on mobile tethering [using a dongle.]

The data is especially useful in tracking revenue-impacting trends.  For instance, the textt businesses of operators -- especially in Europe and Asia -- have been hurt severely by apps like WhatsApp, Skype, and FaceBook Messenger.  In fact, many operators have messenger services of their own: T-Mobile U.S. has BobSled; Vodafone has Join.  These are all social messaging/VoIP apps and that’s become a hugely competitive space.

So because Mobidia has hundreds of thousands of apps in its database (and new apps are added all the time), we can provide immediate data on new mobile apps and services, so in this way we can alert a telco to get ready for a potentially big hit to their text business from a certain app.

	Chris, thanks for this nice discussion.  Any plans to work with partners in the future?

Actually we currently have one partner, a major WiFi provider who is supplying a free WiFi finder inside the app.  And that’s a win/win because our app users save money if they can offload traffic to WiFi.

We are also highly interested in having telecoms distribute the solution as their own.  We figure that would be a great way to boost the number of users beyond the 5 million downloads we’ve been able to capture on our own.