Welcome to Part One of the series on How Image Recognition is Shaping The Future of Retail Execution.
We will deep dive into how image recognition-powered retail store analytics can help CPG manufacturers answer essential business questions of the next decade.
CPG manufacturers often wish for a "Retail Nirvana", where gathering accurate retail data from the right store at the right time is a piece of cake. But like all Nirvanas, obtaining accurate in-store retail data, that too with a manual audit process can be elusive.
It is often easy to be a data-rich organization but being insight-rich becomes crucial to make quick retail decisions. The right retail analytics holds the mystery to how your carefully crafted in-store strategies perform in real-time.
With so many companies that build products and solutions that provide you with retail analytics, you may wonder how you can ensure to bring this whole ecosystem together and successfully drive desired business outcomes in the future.
CPG sales leaders want to drive sales, fast!
Their priority is to ensure the proper execution of their in-store retail strategy. And subsequently, measure how it is all executed, why are they being done this way, and how can it be done better.
While on a mission to lift their current stores' sales, they also want to identify and capture new untapped channels of revenue growth to increase their market penetration and stay ahead of their competition.
A significant volume of retail sales still happens in stores, despite the rise in e-commerce channels or the unveiling of jaw-dropping high-tech utopian like Amazon Go stores.
CPG companies are rapidly shifting to higher gears when it comes to the adoption of in-store technologies such as AI, Machine Learning, Computer Vision, IoT, Mobile, and Mobility-led omni channel platforms to track and monitor every SKU on the shelf, every customer touchpoint to record what and why a sale occurred.
The role of AI and image recognition cannot be limited to just providing accurate and real-time insights. It has to manifest as a predictive tool that helps expand your business in the future. But can this be possible? Is AI or Image Recognition advanced enough to provide highest accuracy in data?
Image recognition and complex AI systems can answer some of the pressing questions in every sales team's mind. Let us explore a few of them below.
A. Retail Analytics help CPG manufacturers identify and rectify execution misconducts almost immediately. But, for ascertaining future possibilities, Predictive Analytics in retail can help predict future probabilities and trends utilizing data modeling and mining techniques on the historical sales data.
With time, your AI system learns from a collective experience of your records to provide consistent business outcomes. Predictive retail analytics is an exciting wave to hit the retail sector and physical retail stores will transform in ways never seen before.
Inventory is the price you pay for lack of information
Retail supply chains service stores based on high-level historical sales data in a cluster of stores. When you do not accurately account for demand fluctuations and other market factors, this results in poor inventory management, frequent stock-outs of essential items, and wastage of over-provisioned products.
Demand and supply planning based on historical sales data can hugely benefit retail supply chains in mapping which store needs which inventory and in what quantity. Optimally distributing and fulfilling stores will help greatly reduce inventory wastage and help build a sustainable supply chain.
Determining customer demography and demand patterns can map what niche and sub-niche segments in a specific location to expand your product portfolio, bring personalized products to eagerly awaiting customers and put your money where it matters the most.
By using advanced analytics to monitor consumer behaviors, manufacturers can begin to understand what their customers want before they ask for it.
Customers don't want to be satisfied, they want to be surprised and delighted.
In-store insights can be integrated into business processes and systems to better tailor your product offering, increase relevance and adjust how you serve your customers. This tends to include better customer engagement, improved service level and, therefore, increased sales.
Imagine if you could identify the high selling products of your competitor brands in each store down to every detail. With this knowledge, you can re-strategize your product fulfillment at every store and offer attractive incentives to retailers and sore owners to stock and promote your brand that impact sales per category per segment per store.
Data-driven decision-making could enable CPG leaders to make accurate sales forecasting, identify market opportunities for up-selling and cross-selling of in-demand assortments at a per-store level, conduct price sensitivity analysis, and get the value of money you spend on in-store promotions.
In today’s fiercely competitive market, CPG companies cannot afford to stay complacent about using store analytics to drive in-store sales and open up new channels of sales opportunities.
CPG sector often sits on tons of historical in-store data which they have been collecting ever since the point of the sale went digital. But, transforming the gathered data into useful insights and getting your analytics team up to speed only causes more delay in time and results in lost sales opportunities.
Image recognition or any retail store analytics has to enable you and your team to empower your on-field force to be more of an extension of your retail operations rather than just "data gatherers".
On-the-spot action plans can help field agents fix execution misconducts and increase SKU visibility on the store shelves. This leaves them with more time and energy to build better relationships with the retailers.
Shelf metrics, and competitive intel gathered over weeks or months or years, can help CPG companies predict which store and region has a high sell rate for specific product categories based on customer behavior and on-shelf competitive strategies. This insight helps you understand what is selling, why is it selling and why is your brand not present for customers to choose from.
The world as we know it experiences tumultuous markets due to the pandemic. The profound realization that the very survival of the CPG sector depends on how well you adapt and integrate technology to drive more customers into your stores, ensure customers find and love your products and enjoy the whole retail experience. These are not easy feats to achieve!
The retail world, now more than ever, opens its arms to AI, Machine Learning, and Computer Vision to gather insights on every store, in every location.
Next up on Part 2 - What are the capabilities and features which help you maximise your stores performance and supercharge your sales! Stay tuned!
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