Retail
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What do you get?
Acquire a framework for maximizing revenue with AI-enabled pricing decisions.
What are we going to do for you?
Realize tangible improvements in revenue and cost efficiencies utilizing our platform, which harnesses advanced algorithms and features a holistic and seamlessly integrated design, streamlining processes and minimizing resource expenditure.
Challenge
In the retail industry, it's common for businesses to overlook the value of incorporating data-driven methods when developing pricing and promotional strategies. This oversight can have minimal or even detrimental effects on profitability, leaving companies without clear guidance for making pricing and promotional decisions.
Solution
Omnidata's Profit Optimization Engine delivers a tailored solution designed specifically for the retail industry. It enables the implementation of pricing and promotional strategies that significantly influence revenue, margin, and cost optimization. Leveraging unique analytical frameworks, the platform swiftly generates insights into price and promotion sensitivity, demand forecasts, and optimal pricing strategies on a large scale. These actionable insights are seamlessly integrated and presented in easily interpretable visualizations, empowering retailers to make informed decisions with confidence.
Optimal Price
Optimal price and promotion management using Reinforcement Learning. Find the balance between Everyday Low Pricing vs Everyday Value Pricing strategies
Promotion Effectiveness
Understand Price Elasticity and Promotion Affinity of products and focus campaign efforts on those products that are likely to respond.
Demand Forecasting
Forecasting to shape product life cycle strategies for demand or scope of sales over time.
Business Problem
Pricing and Promotion decisions are often manual and not based on scientific methods to determine the effectiveness, with some studies showing that up to 70% of promotions are ineffective. Managing inventory is a further challenge with 50%+ of companies facing overstocking or understocking. This in a world where only 30% of companies leveraging data proficiently for this business problem.
Solving for accurate demand forecasts over thousands of product SKUs at scale presents its challenges. Having a view of what the impact is from seasonal factors, market indicators, and the effect of price changes and promotions is key.
Solution Approach
The questions from the executives to be answered include, did my promotions work?, and what was the effect on volumes when we changed the price? Demand forecasting techniques using AI have matured and OmniData combines its skill in this area along with years of experience in utlizing cloud technologies, to provide models @ scale. Our Profit Optimization Ecosystem however goes far beyond just applying AI to demand forecasting.
In addition we built a solution for a client to quickly assess the effectiveness of pricing changes and promotions historically. Clients often don't have a view of what the difference in sales would be between a 15% and 20% discount, with some products showing substantially more sales at the higher discounts and other showing a virtually flat sales demand. It also added the dimension of enabling the client to group products in such a way that we can allocate bespoke pricing strategies to different groups. The solution also took the client to the prescriptive side of analytics by providing recommended price architectures with both increases and discounts into the future. Along with optimial prices, suggested promotions were identified over time, with the optimization being calculated to maximize gross profit.
Value Impact
Pricing decisions were implemented using the solution giving an average gross profit increase of 3% over the selected products, with no negative impact on volumes sold.
OmniData also helped the client identify products for promotions that would optimally respond to marketing activity helping to achieve a postive ROI on the basket of promoted items. Added to this our solution helped suggest the most profitable discounts to achieve the largest lift in sales, by reducing the discount levels by 5% compared to the previous rule set to define discounts, increasing the margin further.
Technical Implementation: Data Sources
Data sources for this product included traditional sales information including sale date, product, product categories, price and volumes. Promotional data were limited and OmniData's solution to identify historical promotions using only the price dynamics were successfuly applied to identify the periods of promotions. Furhermore, macroeconomic data was applied to add to the forecasting models.
Technical Implementation: Solution Features
- Calculate OmniData's bespoke Price Sensitivity and Promotion Affinity metrics. These provide immediate insights into product behaviors.
- Apply OmniData's demand forecasting framework to thousands of SKUs to build a predictive view of sales. Our framework allows for products with large volumes sales per day, and also for products with sparse date, selecting the best algorithm dynamically.
- Applied our Optimization algorithms to maximize the Gross Profit per product given demand forecasts, the effects of price changes and promotios
- Output a bespoke set of reports and data tables for the client to incorporate with their current systems in order to execute on prices and promotions.
Conclusion
Our client was able to unlock insights never seen before, across the continuum of data analytics i.e, from descriptive and diagnostic, to predictive and prescriptive. The solution provided immediate value by highlighting different pricing strategies and also provided optimized pricing and promotion decision which led to tangible business value.