The holiday season is right around the corner and more shoppers will shop on their smartphones or tablets than physical retailers for the first time ever. M-commerce sales will account for the bulk of holiday purchases totaling more than $67 Billion. As a digital marketer, business analyst, or advertiser, it’s critical that your business intelligence properly identifies mobile devices and trends.
At ScientiaMobile, we know every device on the planet and are constantly on the lookout for new devices to add to our weekly updates so that our clients’ mobile web experience is always the best it can be. Our investment translates into sales for you.
Not only will more mobile customers shop online than in stores this year, but according to eMarketer.com, smartphone shoppers will generate more sales than tablets for the first time ever. And other trends like REI’s Black Friday closure are still going strong this year. As E-commerce, and more specifically, M-commerce, continues to grow during the holidays, it’s time to refocus your business strategies to target potential customers on different devices.
With our WURFL InSight data analytics product, you can quickly collect and analyze accurate business intelligence that targets the right customers on the right mobile platforms in real-time. See who is shopping, on what device, and target these similar groups of prospective online shoppers. Now business analytics doesn’t have to be an afterthought.
WURFL InSight pairs with other data analytics tools like Splunk, Tableau, Spark, Informatica, Talend, and IBM DataStage for easy use. And our WURFL InSight offers more than 500 capabilities, ensuring that you have all the information possible to make the best decisions for your business. ‘Tis the season of shopping and with WURFL InSight, it’s sure to be a shopping season to remember as you convert more mobile traffic into sales.
Register now to receive our Special 2016 Black Friday Mobile Overview Report. We’ll be reporting on this year’s hottest mobile trends during the holiday shopping season. Here’s the kind of data we’ll be digging into:
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