Introduction to financial forecasts
Financial forecasting is a direct marketing technique that can be used to help:
- set realistic targets at acceptable costs
- get support for your direct marketing campaign initiatives
- compare segments against each other and cull any that are likely to under-perform
- slice and dice the campaign by parameters such as channel and audience segment
- manage the campaign implementation
- score the success of the campaign
The financial forecasting process involves setting up excel spreadsheets that provide a detailed financial snapshot of every segment that you are intending to communicate with as part of the campaign. These details are likely to include:
- Communication channel i.e. direct mail, email, media, partners, retail etc
- Brief description of the audience segment
- Circulation quantity
- Expected response rate
- Expected value per sale
- Expected total sales
- Expected margin percentage
- $ Contribution (after costs of goods sold)
- Expected costs
- Net contribution (after costs)
- Cost per communication
- Cost per response
The most important drivers of success are likely to be response rate, order value, sales, net contribution and net contribution or cost per customer contacted. These become the KPIs of the campaign (key performance indicators) which, following the campaign, can be used to determine whether the campaign and the segments within it, were successful or not.
Within the financial forecasting model, segments can be grouped together by communication channel to help you to easily identify those segments which are likely to be the best and worst performers. Each of the groups then link to a total area that provides a snapshot of the performance by channel along with the overall financials of the campaign.
Once all the opportunities are added into the forecasts you may find that you need to pull the campaign back a bit which may require deleting those segments that are most likely to be the worst performers.
You can also include the test segments within each group and show your different hypotheses depending on a certain type of offer, message or creative execution to a particular segment of customers by channel.
Initally the numbers entered into the financial forecasting model may be based on educated guesses. However, overtime this forecasting process becomes much more accurate.
Once the forecasts are signed off by the relevant parties, campaign tracking sheets can be set up that reflect the targets by audience segment and by channel. The actual results achieved daily can count down against the expected response rate, number of responses and sales targets.
Following the campaign, thorough post-campaign analysis can be conducted to understand the actual performance of the overall campaign by segment and these results can be compared against each other and against the expected forecasts so that the most effective and cost-efficient segments can be easily identified. The actual results of the completed campaign are likely to be used to create the financial forecasts for future direct marketing campaigns, thereby helping to decrease the guesswork over time.