For decades the dark arts of pricing and inventory management have been a drain on retailers‘ resources.
And even then, decisions are often based on little more than an educated guess. Aifora, however, aims to change all this with it’s AI-powered platform.
Here Dion Broeken, chief revenue officer, answers our questions.
Briefly describe the solution’s purpose and USP
Aifora’s retail automation platform enables retailers to optimize their pricing and inventory management across all channels and to automate the underlying processes. Using artificial intelligence, the aifora platform forecasts consumer demand per article, location and channel in order to make optimal merchandising decisions. This enables retailers to boost revenues and profits, minimize excess inventory and maximize efficiency. Our SaaS solutions are quick and easy to integrate, individually configurable and deliver a return on investment within a very short timeframe.
What exactly would a retailer get from investing in this solution?
Our AI powered platform enables retailers to ensure that the right products are being sold at the right place at the right price – based on accurate demand forecasts in real-time. As a result, retailers enjoy significantly higher revenues and profits. Moreover, stock-outs are avoided – ensuring a better customer experience – while overall stock levels are simultaneously reduced. Also, retailers are able to quickly and flexibly react to changing market conditions, helping them to be proactive rather than reactive. Lastly, our solutions maximize efficiency by automating key processes, enabling retailers to focus on strategic priorities rather than repetitive tasks.
The aifora retail automation platform covers all aspects of pricing on one platform, including initial pricing, markdown pricing, dynamic pricing and promotion planning, as well as all aspects of inventory management, including allocation, replenishment and transfers.
How does it work?
Retailers integrate data from their internal systems onto our platform, e.g. transaction, article and stock data from their ERP system. This data is enriched with external data, such as weather, event and competitor data. Using this pool of data, aifora’s machine learning algorithms forecast demand per SKU per location per channel in real-time, in order to make optimal pricing and inventory decisions. Each retailer’s unique strategies and business rules are taken into account. Via a web interface, users have a transparent overview of all decisions made by “the machine” as well as their impact on central KPIs. Users then have the freedom to accept or override these decisions and to decide on the degree of automation.
Smaller retailers, or those who simply want to profit from even more accurate predictions, can opt to anonymously share their data with others on our platform. The larger the data pool, the more accurate the forecasts and therefore the better the decisions. We call this collaborative machine learning – the transformation of shared data into intelligent actions.
What is the biggest problem/pain point this tech solves?
While the online giants like Amazon & Co. are growing exponentially, most traditional retailers are struggling. They lack the competences and resources to data-drive their business and are therefore not exploiting the full potential of their business. Our AI powered solutions enable retailers of all sizes to make data-driven decisions and therefore offer the right products at the right place at the right price. As a result, retailers can significantly boost profits and maximise efficiency and thus remain competitive in today’s changing market environment.
What is the average time to generate a return on investment?
Retailers generate a return on investment within three to six months of implementing our solution. This is possible through our “pay-as-your grow” subscription model.
What’s been your best client success story?
One of our clients – an omni-channel fashion retailer with stores across Central Europe – was faced with a sell-through rate and turnover that fell below expectations. At the end of each season they were left with high levels of excess inventory and a large quantity of old merchandise had to be transferred into the next season. The underlying problem: the retailer was still reliant on outdated tools and manual processes to manage its pricing.
After a brief onboarding and integration phase of just six weeks, a proof of concept was launched, in which aifora’s markdown optimization solution was implemented for select product groups. During this phase the users became familiar with the solution, internal processes were adapted, and the solution was further optimized based on the users’ feedback. Subsequently the solution was rolled out across all product groups, all stores and all countries. Aifora’s solution ensures that for each and every article price markdowns occur at the right time in the right amount. Since transparency over the pricing decisions is provided via the web interface, users were able to quickly gain trust in the system and increase the degree of automation.
The results were significant: an increased sell-through rate, increased turnover and a reduction of inventory. At the same time, the client is now empowered to quickly react to changing market conditions, thanks to real-time forecasts and automated processes. As aifora’s machine learning algorithms learn continuously, the results will only get better in the future.
Which kinds of retailers would get most value from this?
Medium to large omni-channel retailers who have many SKUs across many locations. Thanks to the flexible configuration options and the value-based pricing scheme, retailers from across all industries can profit from aifora’s solutions.