Between 2012 and 2013, Twitter’s fastest growing demographic was between ages 54 to 66, growing at 79% (Buffer, 2013). Women make up the highest percentage of gamers (IAB, 2014), while sub-Saharan Africa is now the world’s largest mobile technology market (Gallup, 2014).
These statistics fly in the face of conventional wisdom about consumer behavior.
Points-based loyalty systems, introduced by airlines over three decades ago, transformed the travel industry overnight. The prospect of a free trip to a dream city was enough to entice customers to stay loyal to an airline. It was just that simple.
Over two thirds of the UK adult population are active online banking users, and 30% are using mobile. So why is the Financial Services industry still in last place when it comes to delivering on customer experience expectations? The requirement for a new business model that reflects the modern consumers’ lifestyle has never been more evident.
Traditionally in the UK, Boxing Day has been known for luring in millions with post Christmas deals but, according to our latest research, Black Friday is the one retailers need to watch.
Many businesses view re-platforming as a necessary evil in order to keep up with consumers’ demanding shopping habits. And it ain’t cheap. Selfridges recently spent $40m on a new ecommerce platform designed to be future proofed for omnichannel personalization.
Up until recently the event of purchasing a platform was cyclical in nature - every three years a business would embark on a new vendor selection process, then set about lengthy integration and training programmes to get the new system operational and optimized.
Personalization can be scary. It’s understandable; suddenly the anonymous internet knows your personal details, likes, dislikes, and your location….a tad stalkerish? Yet personalization, when done intelligently, can have the reverse effect. Here we look at some examples of personalization that don’t just help the user, they make them feel at home.
As Retail UK gears up for Christmas it may wish to heed a warning from the Ghost of Christmas Past. A massive retail opportunity was wasted at Christmas last year. At Qubit we’ve looked into what our unified visitor data hub could tell us about both consumer shopping behavior and retail responsiveness during the 2013 Christmas period.
The bad news? We found that UK retailers walked away from a massive £1.5bn by neglecting to properly personalize their offers to online visitors.
Media mix optimization has become increasingly complex as advertisers plug into a growing selection of ad exchanges and harness the technologies created to take advantage of the new inventory. DMPs (data management platforms) in particular have been a blessing for advertisers aiming to drive as much qualified traffic as possible at the lowest possible price. The algorithmic spend optimization inherent in DMPs ensures that marketers need only plug into yet another ad network or managed service and let their DMP guide their DSP (Demand Side Platform) to optimal spend allocation based on predefined CPA goals and audience targets.
A/B tests are an excellent way to learn what works and doesn’t work for your website. But after running a test and measuring an effect, a common question is, “why did that happen?”. Maybe a test that sounded like a great idea actually created a downlift and you want to know what went wrong.
At this point many people reach for “post-test segmentation”, taking the test data and splitting it into different user segments, to see if the test had an unexpected effect on some group of users.