Visitors and customers of an e-shop have different behavior regarding type and number of products they purchase, time they stay in the website, how many pages they view before they buy e.tc. We will categorize visitors for the purposes of filtering those results and even adding personalization to the user experience. One more specific example could be the segmentation of “Top Buyers/Purchasers”. We will identify top customers who have purchased products from the e-shop before, and might be as little as 1% of your customer base but can spend as much as the bottom 50% combined. These visitors are definitely worth your time and we want to make sure that you’re optimizing their experience to the fullest.
Customer Segmentation
Product Recommendations & Personalization
E-shops need to be able to learn from their users, collecting data about their tastes and preferences.
Over time and with enough data, we can use machine learning algorithms to perform useful analysis and deliver meaningful recommendations. Other users’ inputs can also improve the results, enabling the system to be retrained periodically.
Roughly the steps of this process are outlined below:
Step 1: Combines data from purchases, wish lists, shopping cart
Step 2: Uses collaborative filtering and product similarity for recommendations
Step 3: Exposes predictions to customers when browsing or buying
We can recommend relative products, products that might interest a visitor, products that have been purchased from a customer that are now on sale.
We can use recommendations in various places/zones/areas on an E-commerce site.
Some of our recommendations:
- Based on products purchased
- Based on products added to cart
- Based on products added to Wishlist
- Based on products visits
- Based on products purchased and now are on sale
- Products with highest rating
Manage Inventory
Inventory forecasting is the process of predicting customer demand for an inventory item over a defined period of time. Accurate inventory demand forecasting enables a company to hold the right amount of stock without over or under-stocking, for optimum inventory control.
We do make sophisticated predictions about future sales, and inform shop owner about what items to order and in which quantity.
Cross Sell Suggestions
Show the customer (in the eshop, or with remarketing) products that he may like, not just what he has seen or buy already.
Sales Prediction
Sales prediction for Seasonal products
Prediction for the sale curve of seasonal products could significant improve the revenue with the correct pricing, and reduce the cost with better stock management
Sales prediction for products Never sold before
In industries like fashion, products change periodically, but shopping behaviour can be predicted and shop owners can make better, informed decisions as they prepare their new catalog.
Sales Statistics
We analyze sales statistics and can get useful insights on things like:
1. One-time buyers vs Returning
2. Customer LTV
3. Average order value
4. Average number of orders per customer
5. Revenue per visitor
6. Cart abandonment rate
7. Checkout completion
We also collect and combine information from various sales channel, like Google AdWords, Google Display campaigns, Facebook Ads and various other marketplaces.
All this information will be used to more accurate calculate the marketing cost per product or per transaction.
Taking into account the profit margin, the system can advise the shop owner about the correct bidding (for ads or display campaigns) for each individual product or category or landing page.
Landing Pages
We can create dynamic landing pages which adapt to each visitor in real time, using a comprehensive visitor profile from multiple data sources and an array of personalization tools.
Pricing Suggestions
Recommendations on price optimization will occur at the SKU and Category level. The recommendations are based on certain online store data (base price, stock, promos, demand, number of sales, other rules). We will also offer the option to store owners to offer customized prices to a certain group of customers.
