Web vs. Mobile Analytics
What web analytics won’t tell you about your mobile customers
Medio, Inc.
One Convention Place 701 Pike Street, Suite 1500 Seattle, WA 98101
www.medio.com 206.262.3700
May 2013
Web vs. Mobile Analytics: What web analytics won’t tell you about your mobile customers
www.medio.com Copyright © 2013 Medio, Inc. 2
This guide will show you the details for engaging with and measuring your mobile customers.
Your web analytics platform isn’t telling you everything you need to know such as their identity (due to their use of multiple mobile device types), location, detailed in-app behaviors, offline usage, buying behavior and context from their other purchase channels.
Introduction
Mobile Marketing and Web Analytics – Square Peg and Round Hole
A Profile of the New Multi-Channel and Mobile Customer
Consumers are engaging with organizations on mobile devices in greater numbers every month and are doing so from locations beyond the desktop computer. Marketing departments need to evolve how they measure and communicate with their mobile customers in this changing consumer landscape. Web analytics platforms aren’t capturing the information companies need to analyze their mobile users and how they interact with apps and advertising. The companies that implement the proper mobile analytics toolsets will have a distinct advantage over their competition because they will serve the right content in the format designed for specific mobile devices. Relying on analytics tools that were originally designed for browsing from a personal computer do not give the information that businesses need to compete in an expanding universe of smartphone and tablet users.
The retail and travel web sites that Nancy visited for this trip all used legacy web analytics tools gathering information. To these platforms, Nancy’s mobile visits weren’t linked to her when she was shopping from her smartphone, laptop or iPad. Both e-tailers missed much of Nancy’s mobile research and several opportunities to promote specials on travel packages and new ski equipment. Neither learned enough about Nancy’s preferences or what she is most comfortable purchasing from her phone or laptop.
Nancy is a financial executive that lives in Chicago and frequently travels to San Francisco, New York and London. She spends half of her working month in her Chicago office and frequently works from home. Because of her busy lifestyle, she relies heavily on her Android smartphone and Apple iPad. She often commutes to work by train and also spends hours each month in airports and hotels. She relies heavily on her mobile devices to help with booking travel, reading the latest news, shopping, and even playing occasional puzzle games to help pass time. She often uses multiple devices for work and personal browsing.
Nancy was preparing for the upcoming holiday season by planning a family ski trip to Steamboat Springs. This was the year Nancy was going to get new ski gear and she was excited to treat herself to new Atomic skis and Nordica boots.
She researched ski recommendations online from her laptop and iPad. For two months, Nancy researched resort and spa vacation packages and monitored airfares on a daily basis. Nancy was also looking for a new GoPro camera that her boyfriend could use to record his ski runs. She downloaded several travel apps and also responded to one specific advertisement for ski helmets when she was researching skis.
Web analytics platforms do not provide the detailed analytics for mobile user behavior and engagements.
Missed Information Means Missed Opportunities
In December 2012 Mary Meeker, a Managing Director at Kleiner Perkins and long time market analyst, shared her Internet Trends Update estimating that there are 1.1 billion smartphone users globally, and that number is expected to grow over 42% annually (Source: Mary Meeker 2012 KPCB Internet Trends Year-End Update). In the US, smartphone and tablet usage continues to grow at a blistering pace. Mobile users are increasingly untethered to a LAN or a Wi-Fi hotspot and they access more content more often from practically anywhere in the world.
The mobile web offers new ways to provide dedicated portals or mobile storefronts with highly specialized user experiences. Mobile apps provide even more specialized experiences as well as new ways for companies to generate revenue. The new challenge is using the right tools to measure mobile users to fully understand and predict their behaviors.
During the day, users often check into the world with their smartphone from home or the local coffee shop on the way to work. When users are working they are often working concurrently on multiple devices such as tablets and laptops. This activity can occur 24 hours a day from an infinite number of locations. These users can access your app or site from different devices and different locations over a period of time. However, your marketing department most likely doesn’t have the tools in place to predictably understand what they will do, when, and how often.
Web analytics platforms do not provide the detailed analytics for mobile user behavior and engagements. In order to acquire, retain and monetize mobile users, organizations need to understand the context of mobile behavior, the devices used, the desired experience, location, and how they purchase.
Meeker also pointed out that we spend 10% of our media time on our mobile devices, but the entire advertising industry only spends 1% of its budget in the mobile channel. Even parts of developing countries in Africa are showing incredible mobile smartphone growth rates.
In India, mobile Internet traffic surpassed desktop Internet traffic for the first time in May of 2012. (Source: StatCounter Global Stats Nov 2012) iPad growth has been 3x faster than the iPhone (Source: Apple). Overall, global Android phone adoption has been over 5 times as much as iPhone (Source: Gartner, Morgan Stanley Research 2012). Mobile monetization is also experiencing a boost including revenue growth from both app purchases and advertising. At the end of 2012 mobile revenues reached almost $20 billion with 67% of that spending on apps and 33% on mobile advertising (Source: Gartner, Mary Meeker 2012).
Location, Movement and Context
The essence of mobile customers is they can browse, research and buy from practically any location and any device. And mobile users will flock to the sites and apps that make it easy for them to get the information and experience they desire. Companies can no longer count on the majority of their users to be tethered to a personal computer or laptop. Mobile users are everywhere and accessing information more freely than ever before. They move frequently and they rapidly make decisions on what they see and hear.
Web analytics platforms are designed to measure activity for users that come from a single location. These platforms measure stationary user traffic very well. They can track where users come from, search terms, page views, referral sites, how long a customer spends on a site and more.
However, web platforms cannot effectively measure the same user who came to a site from their office in the morning, then had a series of return visits on their smartphone or iPad. The context of the visits across the different mobile platforms and the desktop are not analyzed together.
Web analytics platforms lack the sophistication to effectively identify and then track mobile users and their movements.
Web vs. Mobile Analytics: What web analytics won’t tell you about your mobile customers
www.medio.com Copyright © 2013 Medio, Inc. 4
• Location: Country, Region, Province/State, City, Neighborhood - By device type
• Mobile Usage: Researching, Shopping, Showrooming, Spontaneous Buying, Playing – By device type
• Usage Type: Percentage Use by Phone, Tablet, App, Mobile Web
• Movement: Where has the mobile user traveled from, when, and what information are they consuming on the mobile device?
• Detailed App Usage: Sessions, Navigation, Feature Usage, Content Preferences – By time and location
• In App Behavior: Navigation, Content/Feature Access, Offline Usage, Purchase Events
• Channel Preferences: Identify geo-location preferences for apps, products, content, and services
• Demographic Profile: Targets the right content to the right mobile device at the right time
• Usage Type: Percentage Use by Phone, Tablet, App, Mobile Web
• Mobile Advertising Targeting: Ad preferences by device type and location
• Purchase Behavior: What are mobile users most likely to purchase? And how often? And how price sensitive are they when they do purchase?
Mobile Marketing Analytics - Data Points for Location, Movement and Context Shows Detail
Mobile Marketing Analytics – Data Points for Segmentation of Mobile Users Shows Detail
Customer Segmentation
Customer segmentation leads to mobile marketing success. Web analytics platforms can offer basic levels of segmentation. But true segmentation will differentiate how customers browse, research and buy on mobile devices. Mobile marketing analytics platforms will also help aggregate and analyze the users who browse information from both their laptop and mobile devices, allowing retailers and web app developers to deliver a unique experience with customized content. Unfortunately, web-based analytics platforms only look at basic levels of mobile data with limited capability in segmenting their mobile behavior.
With the right geo-information and mobile segmentation you can target campaigns to customers based on what they will most likely purchase. Predicting these mobile purchase patterns requires the collection of specific user data that web analytics typically don’t track.
Customers using desktop or laptops are simple to identify. The power of the tracking cookie makes the customer – as well as their browser activity such as logins, sessions and page views - easy to measure. Laptop and desktop computers, however, also have limited movement and are restricted to specified access points. Therefore, web analytics platforms haven’t had to track movement. Mobile users use their devices wherever they go – standing in line for coffee, at the airport, on lunch breaks, and even from the beach when on vacation. Location information is valuable to help companies better geo-target their valuable content, advertising and app services. Web analytics platforms lack the sophistication to effectively identify and then track mobile users and their movements.
Predicting mobile purchase patterns requires the collection of specific user data that web analytics typically don’t track.
Learn More About Medio
www.medio.com
www.medio.com
[email protected] Twitter: @medio
LinkedIn: Medio
About Medio
Medio is the world’s largest provider of predictive app analytics and the leader in optimizing the lifetime value of mobile customers. The company currently tracks and analyzes over 1 billion events every day and presents over 4 billion recommendations each month to mobile users of the world’s largest brands including Rovio (Angry Birds), Verizon and the Otto Group. The company is focused on retail, media and mobile operators. Headquartered in Seattle, Medio is profitable and privately held. Medio’s investors include Accel Partners, Frazier Technology Ventures, Trilogy Partners and Mohr Davidow Ventures.
• Device types: iPhone, Android, iPad, Kindle, Windows
• Manufacturer / Platform
• Service provider
• Geo-location
Mobile Marketing Analytics – Important Data Points for Tracking Devices
• Memory / Other performance related device features
• Screen size and resolution
• Data services
• Text / Push Notification enabled
Conclusion
The mobile customer promises to generate the greatest number of touch points – and therefore offers the best opportunity for understanding, insights, engagement and most importantly, monetization. When building out your mobile strategy, you should seek an analytics platform specifically designed and built for mobile – with the ability to accurately identify mobile users across multiple devices and fully understand their specific mobile behaviors.
Identifying and Tracking Mobile Customers
Web-based analytics platforms identify users through login IDs and DNS addresses. Most web platforms only identify that a mobile device was used without distinguishing between iPhone, iPad, Android, or Kindle devices – or being able to identify its user. Understanding the breakdown in devices – and their usage – and matching that to a non-registered user helps identify how to deliver the best mobile app experience to that user. To personalize the experience, web-based platforms rely almost entirely on cookies for tracking behaviors on sites. The problem is cookies don’t exist for mobile applications making web analytics platforms deficient in measuring past activities and predicting future trends and opportunities. A mobile marketing platform using large scale matching analysis to identify and track customers across different mobile devices provides a full understanding of a mobile customer’s activities. By understanding the devices customers are using, mobile application strategies can focus on serving the right content in the most entertaining matter for the right platform.
