Today’s big data-driven marketplace only has room for the fittest.
This sounds a little scary, I know. For a long time, mastering the art of accurate and effective number-crunching was no small feat. Over the last decade, machine learning has grown and matured from a flashy high-tech tool to a business essential. But too many retailers still fail to acknowledge the incredibly positive impact artificial intelligence (AI) and big data can have on their businesses and are suffering as a result of their sluggishness.
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AI is no longer an angsty teenager waiting to be taken seriously. It is fully grown and powerfully important. The sooner retailers understand this, the sooner they can leverage its advice and insights to their benefit — and there are a LOT of those. I’ll get to that in a minute, but first I need to make one thing clear. Investing in AI is not a luxury, it is something all retailers must do if they want to survive — and thrive — in today’s tech-savvy market.
Until now, most companies who (wisely) chose to take the plunge and invest in big data did so by outsourcing the work. While still a viable option, outsourcing is no longer the only choice for AI newcomers. As machine learning becomes more ubiquitous, its developers are working to make it more accessible to everyday employees who aren’t necessarily trained in extracting information from data. This is where the term digital insourcing becomes important. In short, it means that your trusted employees use offsite software subscriptions to make informed business decisions with ease and clarity. It is empowering, and retailers across a huge range of industries are taking notice.
Now let’s get to the juicy stuff: what exactly can digital insourcing software platforms do for everyday retailers, from corner stores to massive chains? AI comes in many shapes and sizes, but tools that retailers tend to find the most useful answer the following questions:
1) Where are the best locations to open up shop?
Until very recently, there was no right way to answer this question. Retailers relied on word of mouth, imprecise and out-of-date government data and gut feelings to pick new locations. Seasoned business owners know that almost every aspect of revenue comes down to location, thus every new site is a huge source of risk. AI can literally show you on a map where the most profitable markets are, and within those, which specific locations and sites would be the most profitable for your unique business.
2) Who do we serve?
The success of any retail shop hinges on a thorough understanding of its customer base. With incredibly granular and current demographic data (think education level, mean income, average age, ethnic makeup and so more much), retailers can adjust inventory, create more effective advertising campaigns, and brainstorm better sales strategies.
3) What can we optimize— and how?
AI can help your business massively in unexpected ways, even in the most basic operations. Take Target for example, which recently utilized artificial intelligence to adjust its business hours and number of checkout lanes for optimal speed and revenue. These powerful statistical machines provide real, actionable solutions when it comes to saving time and money (and making a whole lot more, too).
The right platform will leverage a site or chain’s unique data combined with a substantial mix of comprehensive global and local data sets. Some platforms can even calculate, based on the certainty of the parameters at play, exactly how confident users should be in its suggestions. More often than not in today’s leading AI platforms, confidence levels are extremely high. The more data a business collects and feeds into the platform, the higher the confidence level grows. This is not guesswork — it’s the closest humanity has come to predicting the future.
Remember that capitalist markets work by natural selection. And natural selection is never a stronger force than in times of huge environmental change (Darwin can tell you this). In the words of Laura Davis-Taylor , retailers today either evolve or die. Learn how to let the robots work for you, or fall far behind in the retail rat-race. The choice is yours, but the proof is in the pudding: robots can do data better. Why not let them?