SALES & PLANNING
Sales resource allocation: match effort to potential
Sales resource allocation with TIMi compares the sales potential estimated by a propensity model with the actual sales of each shop, region or customer segment, to reallocate the sales force and set grounded commercial objectives.
Potential by location
Estimate what each shop or region should sell.
Gap to actual sales
See where sales fall short of, or exceed, the estimate.
Explained estimates
Each potential comes with the factors behind it.
HOW IT WORKS
How sales resource allocation works.
Three steps, in one engine, on a standard server with no cluster.
1. Prepare the data
Anatella gathers sales by shop, region and period, and the profile of the customers in each area.
2. Estimate the potential
Modeler builds a propensity-to-buy model and estimates the sales a shop or region should reach given its customers.
3. Compare and allocate
The estimate is compared with actual sales, which shows where to reinforce the sales force and which objectives are realistic.
Anatella
ModelerGETTING IT RIGHT
Choices that shape an allocation model.
The gap between potential and sales is a question to investigate, not a verdict.
Potential is not a target
A gap can reflect local conditions that the data does not capture. Treat it as a question to explore with the field team.
Choose the unit of allocation
Shop, region or customer segment. The finer the unit, the more data each unit needs to support a stable estimate.
Objectives stay a management decision
The model gives a reasoned starting point. The commercial objectives remain set by management.
EXPLAINABILITY
Objectives that can be discussed.
A potential figure without reasons is hard to defend in front of a sales team. A white-box model shows which customer characteristics drive the estimate for each shop or region, so objectives can be discussed on facts.
For sales managers
See why a region is estimated to have more potential than its current sales.
For the field
Objectives come with the factors behind them, which makes them easier to discuss.
For model owners
Modeler’s built-in Drift Report shows when a model loses accuracy, so you update it when needed instead of on a fixed calendar.
DATA
What data an allocation model uses.
Anatella connects to more than 80 sources, so this data can be gathered without prior custom development.
Sales by shop
Actual sales by shop, region and period.
Customer profile
Age range and characteristics of the customers in each area.
Products
Range and prices.
Geography
Region and location data.
PROOF
Allocation at store scale.
We do not have a published case study dedicated to sales force allocation. The reference below is indirect: it shows the scale at which store-level scoring runs.
63 products scored across 300,000 stores
Not documented as an allocation case. It shows the scale of store-level scoring: 63 products, 300,000 stores, 2.4 million scores per second on a single platform.
FAQ
Common questions.
Does it replace our sales planning?
No. It adds a data-based estimate of the potential of each shop or region to the planning process. Decisions stay with your sales management.
What level of detail is possible?
Shop, region or customer segment, depending on the data available. The finer the level, the more history each unit needs.
Does it work for B2B accounts?
Yes. Propensity models apply to B2B as well as B2C, provided account-level data is available.
How much history do we need?
Enough sales history per unit to estimate a stable potential. With short history, estimates are indicative.
RELATED USE CASES
Keep exploring.
Lead Scoring
Rank leads by their likelihood to convert, with the reasons behind each score.
Marketing Mix Optimization
Find how to split a marketing budget across actions to maximize expected profit.
Demand Forecasting
Estimate future demand per product and see what drives the forecast.
SEE FOR YOURSELF
Test it on your own data.
Run TIMi on your own data with a free trial, or talk to us about your case.
