| Licence: This feature is part of REC Advanced Edition and requires a a licence upgrade. Please contact us for details. |
Product Lifecycle & Forecast reporting allows you to analyse products from their launch date to understand where they are in their product lifecycle in terms of orders, revenues, profit and when stock will run out based on average number of sales per day. Use this information to determine production / re-ordering levels, extra marketing, price checks, clearance and discontinuation.
This information can be viewed at an individual product level or for a range of products based on launch date.
1. Product Lifecycle Information At A Product Level
This gives you a clear view of where the product is within its lifecycle and the effect of running promotions as either special prices or via coupon discount codes.
- Marketing teams can use this information to plan when to run promotions to reinvigorate sales or towards the end of a product's lifecycle.
- Share this with product development teams to analyse results against the original business case and whether to launch 'new, improved' versions of the product.
- Pass to the pricing teams to see how pricing decisions made at launch and afterwards have affected sales.
See where the product is within it's lifecycle and take action to extend its life or run a clearance sale:
To access this:
- Go to Product manager and select a product
- On the product record click the Orders tab
- Click the 'Product Lifecycle' bar
Add More Insights With Price Comparison |
2. Product Lifecycle & Forecast Report
This report allows you to analyse multiple products at once based on entering a launch date.
Running & Interpreting the Product Lifecycle Report
Access via Reports > Product Lifecycle & Forecast Report
Select products from a particular launch date
Select orders from a particular date
By running the report and selecting orders within different timeframes you can work out how quickly a product is shifting and whether it's a Runner, Repeater or Stranger and organise production / re-ordering as appropriate.
For example, using average sales per day and running orders with different timeframes would highlight:
| Timeframe | Measurement Use | Actions |
| 1 week & 1 month | Identify 'trending' products not related to launches or promotions Performance of new product launches Early bird take up rate Exclusive offers take up rate Measure short promotional periods like Black Friday, Christmas, Easter, Bank Holiday weekends Effectiveness of recent price drops Effectiveness of promotional marketing | Production/procurement would be ready in advance of most of these activities, unless it's a trending product which would need to be: 1. Price checked first as it may now be too cheap or competitors are out of stock 2. Added to the make/re-order schedule if running low on stock 3. Run extra promotions to maintain sales of in-demand products |
| 3 months & 6 months | Analyse seasonal sellers & shift to next seasonal products Analyse Runners, Repeaters & Strangers | 1. Update make/re-order schedules 2. Run promotions to maintain sales or clearance of seasonal products 3. Switch promotions between northern & southern hemispheres if seasonal products |
| 12 months or longer | Analyse Runners, Repeaters & Strangers | 1. Check web visits and conversion rates of low sellers & price drop as part of clearance 2. Discontinue Strangers after trying to clear first. |
Predicting Out-of-stock Dates
In all timeframes, you can use the Predicted Stock Out Date in the report which is calculated on average daily sales and the stock quantity held in the system to give you a prediction of when stock will run out. Bear in mind seasonal fluctuations affect this so shorter timeframe selection for orders will be more meaningful.
What Selection Criteria Is Used In This Report
This report selects products which have a valid live date*
This includes products that were being launched then subsequently set to draft or deleted
It uses successful order lines (e.g. despatched order lines on an order but not returned products)
It will show products with zero orders as well
It works at product level not variation level
*live date functionality was added 31st January 2022; products added before this date had the live date backfilled from product added date. If product added dates were deleted/overridden during imports then the date will probably be 00-00-0000 which is not a valid live date and so those products would not appear in this report unless a special database update is run to backfill the data with the first date a product was added to basket.
Mean Time Between Orders (& At risk customers)
This is another useful metric you can use to understand customer buying patterns and whether some customers are at risk of going away.
This is handled in the separate Users Making Purchases Report with the At Risk column showing how far past their average ordering time a customer has gone e.g. a level of 2 would mean they haven't ordered in twice their normal time.