This is an announcement placeholder
This is an announcement placeholder
The largest cooperative in the Spanish Mediterranean with 790 stores and over 3.5 million customers were able to deliver delightful customer experiences resulting in –
increase in average basket value
improvement in visit frequency
The client is one of the largest electronics retailers in the world, offering thousands of products across multiple categories such as personal computing, imaging/printing, and computer accessories through its network of exclusive and retail partner stores.
The eCommerce division of the firm was facing multiple challenges with respect to its promotions and pricing strategy.
The implementation of social proof delivered compelling results.
Delivering seamless offline and online engagement is difficult, but with Algonomy’s single unified recommendation engine, you can engage customers with automated personalized recommendations, offers based on 150+ out-of-the-box strategies, seamlessly across offline and online touchpoints throughout the customer journey.
Grocers are aiming to reduce average time taken to build the cart and check out under 8 minutes and make shopping experience frictionless.
Build carts faster, simplify buying with pre-built carts based on pastpurchases, brand affinities, customer preferences.
Encourage upsells by enabling one click ‘Buy the recipe’ with personalized suggestions in real-time based on customer behaviour, preferences, and purchase history.
Personalizing for new visitors is a challenge since there is no past purchase history.
Personalize for first time visitors and inspire them to purchase by understanding intent and context like trending products, top sellers of the day/week, products with higher ratings, popular products based on geo location.
Boost or recommend new or long tail products that they may not be aware of from your catalogue using NLP.
Identify your best customers based on RFM models. Also, get insights into churn trends, retention forecasts.
Curate personalized combo offers based on extensive market basket analysis, purchase patterns and behaviour. Increase repeat visitors and repeat purchases by 2x.
Assist visitors discover products faster and increase conversions by 30% by individualizing search results based on attributes like size pack, price band, product type, ingredients.
Localize assortments based on sales forecast, seasonal trends, purchase patterns and weather.
Analyze attributes like shelf duration, weight and date to optimize fresh produce inventory and sales.
Strike a balance between manual and automated merchandising. Assist Merchandisers with faster replenishment using real-time auto-optimization and custom strategies created manually.
Predict out of stock and prevent lost sales by atleast 5-10%
