The shopping spree of November and December is already over. Retailers worldwide are exhausted by all preceding processes and tasks up until the final execution. However, a big question will remain when we take a deep breath, prepare the reports, and close the Q.
Is there a way for retailers to make that high season easier?
The simple answer is yes and is delivered by automation. Retail automation is way more than a buzzword or a process mastered by Amazon and Walmart, playing in their league. The McKinsey experts say that automation and analytics have the dual benefit of boosting profitability while also freeing up resources to focus on the tasks that matter (such as new growth opportunities).
This blog post will focus on a few areas where applying automation can give retailers real value in their transformation journey.
Stock Allocation Automation
What, when, where, and in which quantity might be a million dollars question for a retail chain of stores. Retailers know that a particular item might be a hot offer in one location but somewhat lagging in another, just because the consumer preferences and needs are not the same everywhere. On top of this, lead times vary significantly per location, country, and region, especially in times of disrupted supply chains. Therefore, any mistakes in terms of stock allocation directly affect the P&L.
Analytics and automation are decisive here. By examining and modeling data sets extracted of historical sales, any retailer might know what, when, where, and in which quantity. This way, you prevent overstock or undersupply, hence reducing locked capital or missed sales opportunities.
It is not quite easy to automate the stock allocation process, but the benefits of such a solution are worth the effort. This doesn’t mean that a retailer should completely outsource the task to machines and algorithms, not at all. Experienced professionals still have to look at the suggested orders and confirm or reject them. However, we have to emphasize that such retail automation enables experts to be more productive by eliminating or significantly shortening the time required for such repetitive tasks and increasing the output accuracy.
Pricing, Promotions & Markdowns Automation
Retailers are well aware of the stimulating abilities of discounts and promotions. Dynamic pricing strategy affects one of the critical factors in customers’ decision to purchase or not – their price sensitivity. The retail promotions game is challenging, especially if we have a significant number of SKUs on the shelves. It is common for some retailers to generate negligible direct financial results of such discounts or even a net loss by the increased sell-through rates and average transaction value.
This is where retail automation can help with insights and completely automated solutions. Having good amount of data makes possible for a retailer to apply price elasticity models to highlight not just the right products but also the right discount that will have the best effect on the P&L. Even more, the mathematical models can be tuned to work regarding the business goals of the retailer no matter if they are sales increase, profit increase, or average order value.
The sweetest thing is that analytics businesses like A4E can automate such tasks to help category managers play the promotions game more efficiently and quickly by implementing the solution within their ERP system. Such an approach will eliminate the guesswork involved in delivering the best possible price that maximizes the promotion impact on the P&L performance.
Get in touch with us to learn how A4E can provide you with a solution pointing the best pricing for your retail promotional activities tuned to your business and market specifics.
Inventory Replenishment Automation
Bad inventory replenishment decisions often mean hard-won margins are quickly eroded by markdowns or lost sales opportunities. This is why supply & demand management is crucial. On top of this, customer satisfaction in retail is clearly linked with stock availability. To sum it up – if a retailer doesn’t have the correct SKU in the right store at the right time – the business is in trouble when the retail landscape is so dense.
Not that long ago, many retailers processed such tasks with countless work hours of excellent professionals on myriad spreadsheets. Sure, any modern ERP system made the task way easier. Still, they can`t prevent all possible mistakes, and they are not even close to offering the optimal decision regarding business goals and efficiency.
It is also a fact that sometimes people make wrong decisions, have sick days, move to another position, or even change employer while achieving professional maturity and deep process knowledge takes a long time. This is why such strategies often fall short.
On the other hand, replenishment automation relies on variable data sources, including but not limited to daily sales data, historical sales data, lead times data, existing inventory data, etc. Our experience as data-analytics engineers shows no retailer gets better results in the mid and long term than algorithms trained and fine-tuned to perform this particular task. The amount of data and its variables are immense, so the room for costly mistakes is not acceptable in such a competitive market.
Assortment Analytics & Automation
In some retail businesses, especially chains of stores with locations operating in different regions or even states, the assortment analytics should precede stock allocation. The reason behind this is that consumer preferences and behavior are different.
Latest AI techniques can analyze how different factors influence customer demand and product performance and reveal which product attributes matters more, crafting an optimal assortment mix. As a result, the retailer management will be aware of particular consumer preferences and will be able to satisfy them at their best. This is extremely important in apparel retailers where product size is make or break for customer purchase.
Such data analytics insights should be applied in stock allocation and inventory replenishment processes. Adding a layer of automation where algorithms are doing the hard work and experts review and confirm or fine-tune some decisions is a way to significant business efficiency boost that could value in millions.
Shifting consumer preferences from brick & mortar shopping to e-commerce was highly accelerated by the COVID-19 pandemic. This transformation affects almost every retailer, including grocery and hypermarket segments, where omnichannel is more important. The retail industry replied with partnerships with local providers enabling them to execute same-day deliveries.
This is why warehousing automation is becoming more and more important, and if a retailer fails to invest there, the business might be sinking tomorrow or the day after. Giants like Walmart and Amazon master robotic-process-automation (RPA), but recent surveys show that more than half of the retailers plan to invest in fulfillment. In recent research, renowned consulting firm McKinsey states that 64% of the retailers are planning to invest in digitalization and automation.
Retail Marketing Automation
Marketing, retail marketing in particular, is consisted of multiple tedious tasks. No matter if we talk about lead segmentation, customers ‘clustering, campaign management, or else – a lot of the work could be automated. There are many solutions, especially SaaS, addressing this issue.
What they lack are few specifics like sending the right offer to the right customer, which are within the capabilities of data analytics and recommendations engines. Upselling and cross-selling are vital tools to increase AOV indicator, which has a direct and significant impact on the P&L results. Decision automation in this vertical is not just possible but also a must for any retailer who wants to maximize existing customers’ value.