Amazon’s revenue topped $61B in 2012, a 27% increase over its 2011 revenue of ~$48B. A big driver of its phenomenal growth –Analytics! The company has been a pioneer in big data analytics. As early as 2009, it attributed about 20% of its total revenue (~$5B out of $24.9 B) to its successful product recommendation capability from market basket analysis.
Macy’s, another retail giant has publicly credited analytics for boosting its store sales by 10%.
U.K. Grocery giant Tesco has improved its discount coupons redemption rate by a factor of 3.6 by leveraging predictive analytics to customize its offers. The company distributes over 100 million coupons annually at its cash registers across 13 countries.
Target, Great Clips, you see story after story of retailers reaping big benefits from analytics in media.
Then how is it that even today ONLY 12% of retail executives, 83% of which came from companies with revenues larger than $1B, report high level of data analytics literacy within their organization, per KPMG 2013 Retail Business Outlook report.
And if this is the situation in larger retailers, can you imagine the state of analytic literacy and therefore adoption in smaller retailers, who have even fewer resources to spend on attracting and acquiring expensive Ph.D statisticians, quants, and data scientists.
But can the status quo continue? Facing uncertain economic conditions, commoditized products and newer/ever-increasing retail channels and formats, can retailers really ignore the priceless insights hidden within their data?
If not, then how do you bridge the gap between existing skills and business need for data driven insights? In my opinion – the answer lies in simplicity!!
One of the main reasons more retailers have not widely adopted analytics is due to associated complexity of the legacy analytic solutions. When one needs to write 50,000 lines of code to just do simple affinity analysis to understand which products are likely to sell better together so they can maximize customer’s basket size, the chances are that analytics will stay limited to certain pockets of the organization. Such skills are limited -- you just can’t scale the model. Even if you are one of the fortunate large corporations with a team of qualified programmers!
To consumerize analytics, you need a solution that puts the power in the hands of your data analysts. One that allows them to access and combine the data, when they need it, from where they need it. A solution that enables them to perform complex analysis by creating analytical work flows simply by dragging and dropping pre-built modules – without any coding. And then save the analyses to reuse and share with others – via reports or in cloud.
Alteryx provides data analysts that power.
We all know that data is only going to increase, in volume, in velocity, and in variety. Especially as retailers adopt more and more of newer technologies -- sensors to monitor customers’ in-store movements, smart shelves to adjust pricing, video monitors to profile customers based on their ethnicity, age, facial expressions etc.
To derive value from this data--in time to support your decisions --you cannot continue to depend on legacy software providers. They make analytics too complicated and way too expensive for wide-spread adoption. You need a solution that lets you harness the data – quickly and easily –without breaking the bank!
And you need it now! Per Gartner, by 2016, 70% of the most profitable companies will manage their business using real-time predictive analytics.
Can you afford to be left behind?