Big Data in Retail: Top 10 Strategies to Add to Your Cart
Posted by Walid Abou-Halloun Date: Mar 27, 2018 3:00:22 AM
Despite the stock market hitting record highs, the retail industry is under threat with around 90,000 retail workers let go in the last year.
To combat the war on brick and mortar retail, companies are using big data to rebuild their customer bases. Business is changing and big data retail strategies have been the key to making profits.
Retail businesses of every size are using data mining, SEO and online advertising in new ways. There are hundreds of services to help collect data, and to best take advantage of it, retail enterprises need to understand how big data can be a true game-changer.
If you’re new to the world of data collection or you’ve taken a few steps to gather data on your sales and demographics, you need to put together a strategy. Implementing a big data retail strategy can take several different forms. Here are ten of the most reliable ones.
1. Creating Recommendation Engines
For decades, retailers have been asking customers for their phone numbers, addresses, or post codes as these can help link purchase history to a customer profile. Retailers can then start to predict what they might purchase next.
Using machine learning based on this component of big data, retail companies can recommend other products and services.
When you log on to Amazon, recommendations cover half of the page. They take data to determine what other people like you have bought, what you’ve already bought and what you might need to replace.
Where once retailers tried to remind buyers to get batteries or fast food restaurants ask if you want a drink, Amazon has found a way to do this without you noticing.
Recommendation engines can lead to a massive bump in sales while being one of the lowest overhead use cases for big data in retail.
2. A 360-Degree Customer Relationship
A 360-DEGREE CUSTOMER RELATIONSHIP SOFTWARE CAN SAVE YOU HEADACHES.
Customers have high expectations for retail, despite the increasingly thin profit margins. When they visit a shop, they want everything to be in stock, on-hand and at the lowest price.
When there is an issue, they expect to be able to communicate with brands immediately through various social channels. They lodge their complaints on social media and expect a response to their concerns within minutes.
Not every company can keep up with these demands, no matter their size.
Big data retail technology and real-time computing allow you and your customer service team to be in touch with the changing demands of customers.
One mistake could cost your company big time and lead to a big drop in profits.
3. Complementary Analysis
Since retail began, savvy business owners have been trying to find ways to sell more items in every transaction. One of the most common ways is for businesses to figure out which items people tend to buy together or complement one another.
In the past, retailers had to hire people to go through receipts by hand to find out what items to stock and which should be placed next to each other. Data now does the job for us.
Big data retail analysis systems can provide insight into which items should be placed in proximity to compliment sales and the items that would negatively impact sales if placed together. It is this kind of comparative analysis using sales data that help retailers earn more revenue without the need for a lot of manual labour.
Furthermore, these systems show the items that move quickly when on promotion or when items are on sale. No item in a retail environment exists in a vacuum—analytic systems can show how each of the parts contributes to the whole.
4. Showing Customer Paths to Purchase
Understanding the decision-making process for a customer who decides to make a purchase reveals a lot about how your marketing and retail infrastructure is working. There was a time when companies would have to hire services to call their customer base to fill out a phone survey.
Today, this can be done in easier ways.
Through software that can be added to e-commerce websites, retail companies are able to collect data that can show which channels a customer has used to get to your product page and the channels that have a higher conversion rate.
This can help improve a retailers marketing strategy by providing insights on which ad campaigns are gaining traction, where the budget is best spent and where you might find an emerging market for your products.
Social media can also reveal a fair amount of interesting behaviours and methods for understanding the influences that lead to purchases. Using big data, retail companies can follow trending terms, influencers and competitors to develop strategies that will improve click through rates and conversions.
5. Listening To Social Media
Speaking of social media, this new approach to customer interaction has revealed valuable information about how customers engage with brands. Now more than ever, brands have access to hordes of data about their potential and existing customers based purely on who they are following, what they are reacting to and posting about.
Thankfully there are quite a wide range of tools that are available for extracting data from social media for companies to use in their marketing and sales efforts.
However, always be cautious when making decisions based on social media. There, winds can change at a moment’s notice. While you’re crafting the perfect approach to a trending topic, customers could be on to the next trending topic before you even had the chance to roll it out.
Be sure to balance long-term trends with temporary ones to ensure you don’t seem out of touch or behind. Data allows you to understand the experience that your users want before they are even aware of it.
6. Price Optimisation Tools
Retailers no longer have to rely on secret shoppers to scout out competitors or learn about customer behaviour and report back. They no longer even have to leave their office to get the data they need. Most competitors list their best promotions via multiple online channels to reach the widest possible audience.
in such a competitive market, it can be rather difficult at times to decide on the right price.
While some retailers might be able to undercut you for a competitive product, you might be afraid you’ll lose money with such a low price. This is where your big data retail strategy can come into play.
You can look at long-term price trends to see how much customers are used to paying for a product, what kind of complimentary products are included when on sale and other behavioural shopping trends. Using this data you can then develop an automated pricing strategy.
Collecting this data and repricing manually is virtually impossible especially in real time when you are trying to keep up with competitors and market trends. Pricing response time is key and an automated pricing optimiser tool could mean the difference between falling behind your competition or staying relevant to the consumer.
Automated pricing can go haywire though, if gone unchecked. Remember the news when Amazon price bots drove prices for unremarkable items up into the millions due to a glitch? Once you set your system up, monitor it regularly and set up alerts in case of any problems.
7. Leveraging Your Workplace
Labor is expensive—this is what most retailers may cite as one of the factors hurting their business the most. With the help of big data, retail chains can optimise their workplace needs and reshape their staffing budgets.
For one, data can find area sales trends that in-store data might overlook.
A special event at a nearby store could drive up traffic into your own stores. A sudden cold snap could have people storming your site for winter wear. Similarly, an early spring could leave your winter wear sitting on the shelves and your employees twiddling their thumbs.
Using data, retailers can redirect their energy where it’s needed. This explains the rise in customer-operated sales kiosks. The margin of error can be reduced while customer interactions can be more accurately directed.
8. Optimising Inventory
Knowing what your customers will need and when they will need it used to take hours of analysis and involved a lot of guesswork. Manufacturers, suppliers, and distributors would all have to work together to ensure solid coordination. A hiccup in the chain could leave retailers taking the blame when customers needed a product that isn’t on the shelves.
If you’ve got your inventory scattered among different warehouses, you’ll have to know where products will be needed next. If a customer needs a seasonal item in the middle of the country, big data retail strategies can help you determine which warehouse to get it from.
While it might be out of season for your northeast location, your west location might need to have that item on the floor for most of the year. Seasonal inventory decisions depend more on calendar and temperature, and big data retail solutions can help you make the informed choices quickly and efficiently.
9. Rooting Out Fraud
Retailers deal with fraud more than many other industries. By measuring sales history, you can create predictive models that will show abnormalities and alert you to fraud as it happens. Using collections of big data, retail companies can compare their data with historical trends.
There can be built-in models that alert you of financial transfers that reach a certain frequency or dollar amount. You’ll be able to look back on your history to see if everything seems above board.
There’s so much data at the disposal of retailers—their only hurdle is figuring out how to use it against fraud. Regular monitoring is only one piece of the puzzle.
10. Local Marketing
Using swathes of information that has been gathered, retail operations can start targeting their customers
locally. Locally targeted advertising and SEO are the future of marketing.
Marketing efforts
can be catered to post codes by monitoring purchase histories and trends that appear locally. By watching
climate changes, gentrification trends, and age demographic movements, data models will know what sales
trends to expect before anyone else will.
Big Data Retail Strategies Are The Future
In order to stay competitive in the changing world of retail, your business managers, IT departments, marketing, and HR should start to overlap their systems and coordinate.
Using data as it comes in will change the modelling for how to deal with customers, inventory, and old sales models. Combined with automated warehousing, electronic kiosks, and 3D printing, the retail world could be upended any day now.
Keep your ear to the ground to stay ahead of trends. If you’re ready to start implementing big data strategies into your retail business, contact us today.
