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GUEST COMMENT Why the future of retailers will depend on data

Image: Fotolia

Image: Fotolia

The retail industry has always survived on razor-thin margins, and successful businesses must constantly adapt to evolving situations and use new tools to their advantage. As the digital era has expanded, two new tools have come into the limelight: big data (like the kind gathered by social media, Google, and ISPs) and AI/machine learning.

Combined, both of these tools will reinvent the retail landscape and will be required for any retail business that is looking to stay afloat. This is all especially true in Covid-19’s wake.

And all this isn’t to say that retailers have necessarily ignored big data so far. In fact, the opposite is true – companies have been using (and some would say abusing) big data and machine learning for years now. But although some retail companies have taken steps to integrate big data into their existing operations, most of them still make a few key errors:

  • They focus more on big data from past performance, then use that performance data to drive their future decisions. This doesn’t take machine learning and predictive algorithms into account.
  • They focus too much on details in present-day data without looking at macro patterns or emergent insights.
  • They don’t look at signals for consumer demand to make accurate predictions about what their consumers will care about in the short-term future (i.e. 1 to 2 years from now).

Suffice it to say that while big data and machine learning are cornerstones of the retail industry already, successful businesses will need to leverage them even more intelligently in the future. Let’s examine how this might shake out over the next few years.

How big data will help retailers thrive after Covid-19

 Covid-19 has driven many retail businesses to the very edge of profitability (or even bankruptcy). As more and more people shift their buying habits, or outright spend less money because they’re bringing in less money themselves, retail industries will need to account for these shifts in consumer behavior.

After all, even after Covid-19 ends, consumers may maintain the same behaviors, or another pandemic could arrive sooner than we think. Fortunately, big data can help retailers survive and even thrive in a few key ways.

Better understanding of customer behavior

First and foremost, data can offer a better understanding of customer behavior. By collecting data about customer habits, purchases, treatment of receipts, browsing interests, and much more, the retail industry will be able to understand its customers more deeply than ever before.

This, in turn, will allow those same companies to invest in targeted marketing campaigns, promote certain products or narrow down their industry niche for better profit margins, or otherwise make sure that every dollar they spend pursuing another customer is more effective in the long run.

Understanding and predicting consumer behavior is key for any business making big decisions.

More predictive profit models

Another way big data can help retail businesses is by offering better predictive profit models. In a nutshell, this means companies can look at the data to:

  • Determine where their marketing or development dollars are best spent
  • Predict which niches, consumer trends, or marketing campaigns are most likely to be profitable
  • Follow through with those decisions for better success overall

Rather than having marketing campaigns or product promotions with “educated guesses”, big data can help retail industries prioritize their efforts and make smarter decisions that result in even greater profits… all while using real datasets with actual sources aside from human intuition. 

Perhaps most interestingly, this can all be true even if consumers spend less money overall since retailers are becoming better at targeting and capturing sales from their target audiences.

Better customer engagement and loyalty

Lastly, big data will be vital for boosting customer engagement and loyalty: two factors that can determine which companies or businesses retain long-term customer bases and which do not. Today, it’s easier than ever to grow a brand with big data.

In essence, customer engagement and loyalty are more important than ever before. This is doubly true since consumers have more choices for the same product needs than they did in the past and are shopping online more than ever, too. Countless studies and research cases in data science have revealed the best practices for how data should be collected to increase the chance of customer engagement as well, specifically through data visualizations, artificial intelligence and machine learning methods. Speaking of which…

How will AI affect the future of retail?

We haven’t even touched on machine learning and artificial intelligence. These technologies are evolving and becoming more complex every year, and it won’t be long before retail companies (and other industries) start relying on machine learning even more heavily.

More efficient task completion

Machine learning will be particularly valuable for its ability to make rote tasks more efficient and improve productivity across the board. For instance, machine learning and AI can automate many inventory or purchasing-related tasks, and with much more accuracy and consistency than any human worker. 

This, in turn, will allow retail businesses to cut down on their costs and losses and stay profitable even as consumer habits change and if another pandemic eventually affects the global economy.

Fewer laborers required

In addition to all that, machine learning and AI will necessarily free up manpower since companies won’t need the same number of workers to do the same amount of work as they did before. 

This is especially true with low skill or basic tasks or jobs. Examples include:

  • retail shopping centers employing machine learning to handle customer service requests
  • retail online websites employing artificial intelligence to direct customers to the perfect item
  • machine learning and AI handling shipping or coordination tasks where a worker would have been needed before

Offering preselection

But most importantly of all, machine learning and AI will enable true “preselection” for the modern consumer. Preselection, in this context, means that AI will be able to offer up the ideal product or service to a customer before they even browse a retail or e-commerce website. 

For example, many of the most common ecommerce platforms, such as Shopify and Wix, actually come with AI capabilities built into them, including customer-centric search capabilities, cloud-based virtual assistants, and providing a more personalized shopping experience to customers. As a result, customers can be recommended products and services they are more likely to buy 

This is all especially pertinent for the so-called “AI generation”, or those aged between five and nine years old at the time of this writing. This generation has been influenced by AI for their entire lives. They’ll take to AI and machine learning better than anyone and may expect retail businesses to provide them with solutions and products with a minimum of effort. Humans will struggle with this. AI won’t, in part because it will have a vast base of data collected on that consumer thanks to big data.

 

Conclusion

As you can see, both big data and machine learning are working together to heavily influence the retail industry and others as time goes on. The future of retail is undoubtedly dependent on data collection and machine learning. Only time will tell exactly what those developments look like, and which retail companies will be agile enough to adapt ahead of their competitors.

Sam Bocetta is a former defence analyst, now a freelance journalist

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