The Launch Pack manual
A product launch requires a large investment, without a guarantee of success. Therefore, a quick, accurate, and reliable evaluation of a new product is essential to make a product launch successful. Analyses can be performed to determine whether, for example, the innovation itself poses a fundamental, conceptual problem, or whether there are problems with its marketing. It can also be investigated whether an innovation generates growth for a supplier and thereby justifies its existence, and so on.
How do I get started?
Before the analysis is started, we look at the scope of the research: what are the new products and which similar products can we use as a benchmark. Based on this benchmark, we can assess performance and calculate cannibalization.
The study will be available in the report. From then on, you can consult it by opening the report and clicking on the analysis on the first page.
What is the meaning of the different KPIs?
The Launch Pack only analyzes the stores that offer the new product in the last week of the Launch Pack. Products from the benchmark are only included if they have been sold throughout the entire analysis period. We use customer KPIs in this report, so we only perform the analysis on Xtra users.
We start the report with an overview of a number of general KPIs:
- OOP or Out-of-pocket: the turnover based on the price the customer pays (incl. tax and promotions), similar to value at Nielsen
- Volume (l/kg/pc/…): the sold volume
- Units: quantity, measured in the lowest scannable EAN code, measured during the selected period
- Average Price volume: the average price per volume (l/kg/pc/…)
The performance of an innovation is evaluated based on four individual KPIs:
- Out-of-Pocket per 100 shoppers = (Out-of-Pocket of the product) / (total number of Xtra customers at the chain, regardless of whether they bought the new product) × 100
- Penetration = (the number of Xtra buyers of the new product) / (total number of Xtra customers at the chain, regardless of whether they bought the new product)
- Out-of-Pocket per shopper = (Out-of-Pocket of the product) / (the number of Xtra buyers of the new product)
- Repurchase = (the number of Xtra buyers who bought the new product at least twice) / (the number of Xtra buyers of the new product)
To be able to judge whether these performances are good, you can compare the performances of the new product with those of its competing articles. For this reason, the Launch Pack uses a benchmark against which innovations are measured.
What data is in the report?
The Launch Pack consists of 4 parts:
- Weekly general data
- Insight into the performance of the innovation, including benchmark
- Who is the new product appealing to?
- What is the effect on the category?
Based on these insights, marketing events can be developed more effectively, product adjustments can be made, even the production capacity can be optimized, but at the same time it becomes clear whether it is actually worthwhile to continue investing in the innovation.
Sales results per week
Before we start with all the specific analyses to assess the performance of the new product, we start by showing a number of basic KPIs on a weekly basis. This gives the opportunity to see where we stand. You can select two to compare them with each other.
For the repurchase, the result will probably be 0. We look at the results week by week here, and the chance that a customer buys the products twice in a week is very small. It is better to view this cumulatively in the next tab.
Benchmark your results
The top graph shows the cumulative results in the last available period on 4 KPIs.
The blue triangle represents the performance of the new product. All other colors and bars are benchmark results:
- The gray triangle: the average result of the benchmark
- Dark green: performance of the top 25% performing products
- Light green: the performance is between the 25 and 50% best products
- Yellow: the performance is between the 50 and 75% best products
- Red: the performance of the 25% least performing products
The top part of the bar is the product that is just in the top 5% of products, the bottom part is in the bottom 5% of products. The boundary between light green and yellow indicates the median.
At the bottom, you will find a similar graph, but with an overview of all periods together. The graph contains cumulative results, but you can also look at period by period. This can be important, for example, if you had a bad start and you want to check if your performance after an adjustment is now in line with the benchmark.
When is your performance good now?
In general, we expect a new product to be in the green zone. However, there is some nuance here:
- The OOP per shopper: the cost per unit has a major impact here. If your item is priced much more/less expensive than the items in the benchmark or if the packaging is much larger/smaller, then there is a good chance that you will achieve a deviating score here.
- Repurchase: the benchmark contains items that already exist. They usually already have a number of loyal customers. Therefore, we consider being in the top 75% of products as a good score.
Customer profile and cannibalization
At the top, you can see how you score per region (based on the customer’s place of residence) and household type on the Out-of-Pocket per 100 households.
We calculate the score of each group and divide it by the performance across all segments. A score above 1 indicates that the group is overrepresented, and a score below 1 that it is underrepresented. This is done for both the new product and the benchmark, so you can compare whether the buyer of the new product has a similar profile to the benchmark.
At the bottom, we check whether customers who bought the new product have also spent more:
- Expenditure on the new product
- Evolution of expenditure on the other products in the benchmark
- Impact on total expenditure
We apply a small correction here. We take into account the expenditure of people who buy the products from the benchmark, but not the new product. If that evolution is positive or negative, then we correct that in the data. This way, we remove the evolution that would have been there, if the product had not been launched.
List of articles
On the last page, you will find an overview of the articles in the benchmark. All products must also be sold during the analysis period to be included. For each product, we mention a ‘Y’ or ‘N’ to indicate whether the article was included.