According to McKinsey, 7K US stores pulled their shutters down in 2017. In recent years, when the customers turned to online purchasing, business owners noticed the declining sales and footfalls on brick and mortar floors. Hence, the sad decisions to shut shop came into existence.
Had they accounted for the online sales driven through the physical stores, they wouldn’t have taken these drastic measures.
The metrics related to only your shop sales could misguide, according to McKinsey, because users have gone omnichannel. They research the products, check them out for look and feel, quality in the stores, and then move to buy from the online stores.
If your customers have gone omnichannel, why not you? And for measuring your endeavors and improving your users’ experience, omnichannel data analytics is the best thing you should invest in.
What is Omnichannel Retail Experience?
Omnichannel retail puts your customer at the center in their buying journey and renders them a univocal experience across all the touchpoints.
For customers, omnichannel is the seamless experience they receive across the app, website, or store while researching and buying the products. When they switch the channel, they should receive a consistent experience. Buying a bag from a store shouldn’t be a hassle if they have chosen the same from the digital store, for instance.
Omnichannel retail for retailers means creating processes that capture the customer’s moves across every channel. If a customer buys apparel in your store and registers their email address, you should be able to capture both - offline and online information.
Furthermore, your omnichannel system should help you predict the market and offer a holistic view of product performance.
And for this to materialize, you need to employ omnichannel analytics solutions.
What is Omnichannel Analytics in Retail Domain?
Collecting customers’ data from all the channels and then understanding their behavior, likings, grievances, and future demands are part of omnichannel intelligence and analytics.
Omnichannel synchronizes all channels to reflect the same information.
You consider every phase of a customer’s journey: the analysis, research, and purchase of a product for this purpose. Apart from a successful purchase, you also collect data about their visits to stores by providing forms to fill in and share the experience.
While physically checking a product in a store, customers can check the product availability and best price online and even book the product through the app. Additionally, failed product transactions, returned products, and abandoned carts are also taken into consideration.
That said, every move of the users from online and offline shopping and promotional media is merged.
Insights coming out of such a data analytics system cover every aspect of a user’s buying journey. Not to forget, 72% of users prefer retail companies to know their buying journey and behavior.
How is Data Analytics taking Omnichannel Retail to New Heights?
Let’s see the various benefits that signify the analytics role in omnichannel retail.
The key to turn leads into customers and customers into advocates is personalization. Sending targeted emails with buying options similar to the purchase history, messaging via WhatsApp and reminding about the abandoned cart, or advertising the last browsed laptop on random websites: all are instances of personalization.
But how do you achieve personalization? By collecting your users’ data from all the channels. By recording every step they take, whether in physical store or online, and using analytics to your benefit.
Analytics tells you about your users’ special days, like birthdays and anniversaries. This knowledge helps you to personalize your messages. And make no mistake, personalization has shown exceptional results.
According to a BCG survey, customers are 40% more likely to step beyond their planned shopping budget, all thanks to personalization.
Imagine a customer ordered a pair of shoes and a matching bag from your website. But while paying the bill, the transaction failed. If you keep track of their activity and couple data from your physical stores with online stores, you extend an offer wherein they’ll be able to pick the items from and pay at the nearest outlet.
Maintaining precise and holistic data across all the channels aids in sending the right message to your customers. Also, advanced analytics tools like Power BI and Qlik can capture and process real-time data for you to convey the right message immediately.
Once you reconcile your reports across the channels, you get better insights about customer behavior, market pulse, and your stores.
Once you have a bird’s-eye view of your customers’ data across the channels, you can easily segment the customers based on their demographics, sentiments, and activities.
Say, for instance, if your Gen Z and Gen Y customers are active on Instagram and Gen X customers are active on Facebook, you can bifurcate your ads and content accordingly.
Every age group has a preferred channel to reach out to customer service. Youngsters like to hang around social media more than baby boomers. The latter prefers phone and voice-based channels more. You can use these touchpoints to promoting products for their needs.
Technologies like cloud and descriptive and diagnostic analytics help you grab real-time data. Having data at your fingertips from promotions, you can quickly gauge what has worked effectively on which channel and at what time.
For example, when you know that promotional emails work well on weekends while in-app notifications about offers work in the evenings, you can use the facts to your advantage while marketing.
Collecting data and reporting about the low stock and stock out on the shelves helps companies to replenish their inventory on time. Add sensors to the shelves and enable the supply chain with IoT to collecting such information.
You can collect and keep stocks data handy about all stores—physical and online. If a demand can’t be fulfilled at one store, you can still cater to the customers’ request via another nearby store or an online medium.
Replenish all the stocks well in advance or shuffle from one store to another will help you handle the issues, including curbing order cancellations.
Predicting the Future
Dig up the past data and combine it with customer sentiments, their behavior, and market status. With machine learning integrated with analytics, you can remove a lot of guesswork in retail.
The price, quantity, distribution strategy, stock levels, and inventory allocation to stores - predictive analytics can help you visualize several crucial KPIs.
When you take omnichannel into consideration, the data game gets challenging. Predictive analytics handles this when integrated with the ERP system and other data sources. This brings in a holistic picture of data with minute details.
Predictive features in omnichannel retail analytics solutions would also help you analyze a new product launch.
You can predict new opportunities and unexplored marketing territories from historical data, demands, and gap analysis. Predictions can tell whether a new launch would be sold and received well or not. Predictive analytics can also dive deep to find the right customer base for the new launch.
Have you Integrated Your Omnichannel Retail with Analytics?
If not yet, this is just the right time to think about integrating analytics into your retail business. This will help you go omnichannel in the genuine sense and measure your efforts; analytics can also help the C-League team gain a better insight into the business health.
Logesys team can help you implement analytics in your omnichannel practices. You are only a consultation away to take your omnichannel presence to a new level. What are you waiting for?