The use of data analytics is extremely important in tracking the progress of any major industry. In retail, it is basically impossible to properly assess where any given company stands without it. Both in determining the internal dynamics of a particular company, as well as industry developments overall, accurate numbers can only be obtained by means of proper data analytics.
How exactly can this information be used? In quite a few ways, actually. It pays to take a closer look at what the use of data analytics means for retailers and what its benefits are. You can read here for more detailed information on tools to use in your analysis, as well. Let’s examine five uses of data analytics in the retail industry.
1. Future growth patterns and trends
Naturally, every business wants to predict future growth patterns with as much accuracy as possible. Being able to do so helps to determine pricing, manage customer relations, and plan many other aspects of sales. Businesses can see more clearly where they will stand in one, five, or ten years’ time and create plans accordingly.
A related advantage is the prediction of trends in any given market. If businesses can determine in precise numbers the degree to which customers are buying more of certain items and less of others, it will be a huge advantage to them in terms of planning.
2. Targeted marketing
In the past, retail marketing has been more general in terms of the basis for its messaging. Although information was collected on sales numbers and how businesses fared in comparison to each other, the capability for precise analysis on buying choices and demographics only came about recently. These days, businesses can predict the likelihood of a given customer buying certain items with much greater accuracy than even a few years ago. It is even possible to track particular consumers based on their past purchases. Businesses can market their goods accordingly and not waste marketing efforts on misdirected campaigns.
The use of data analytics for strategic marketing campaigns has already proven to be a major boon to many businesses. People are starting to get “perfect offers” without even knowing the degree to which their buying patterns have been analyzed. Creepy? Perhaps. But it works.
3. Price determination
In analyzing customer data, businesses can assess what people of different demographic groups are really willing to pay for goods. In the past, price determination has been calculated according to season, holidays, and other commonly-accepted methods within industries. Now, though, businesses can establish prices based on analytics collected from very subtle pricing adjustments and their consequent results in customer behavior.
4. Inventory management
Every business needs to be able to predict inventory as precisely as possible. In the past, predictions were based on much looser data – annual and seasonal profit gains or losses, larger trends in industry, etc. While these things are still taken into consideration, the much-increased precision that data analytics offers businesses helps owners determine what to stock with far greater accuracy. And this, in turn, prevents them from having to deal with either shortages or surpluses much better than before.
5. Improved planning capacity for small and large businesses alike
Data analytics is used by retail outfits large and small. Big giants like Walmart use it to keep track of the huge numbers of transactions that its stores amass on a daily basis. And small businesses similarly rely on it because they need to figure out what to do to stay afloat in the market. There is a reason why companies like Walmart scoop up such a huge portion of the population. Many people say they prefer the cozy atmosphere of smaller stores but that the giants’ prices are simply unbeatable. Using data analytics, smaller-scale retailers can figure out how they can adjust their pricing, customer service, and marketing to retain the critical mass of customers they need to stay alive.
Analytics is only getting better
The use of data analytics in retail is only getting stronger. These days, businesses are using AI to refine predictions in customer behavior by analyzing preferences almost to a greater degree than customers themselves consciously realize. This, in turn, helps every aspect of planning, from sales pitches to inventory management to determining where a given business stands vis-a-vis the competition.
Any retail business hoping to stay on top of the game needs to start using data analytics lest they risk falling behind. It is beneficial for all retailers, large and small.