1. Overview: The Sales Forecasting Module

What the module does and how it fits into the Confido platform.

The Sales Forecasting module is where Confido helps brands build, maintain, and evolve their volume forecasts — from a granular, driver-based baseline through promotional lifts, new distribution, and shipper/display activities. It is built to replace or centralize the spreadsheet-heavy, manual forecasting processes that most CPG teams rely on today.

The module integrates with your data sources (syndicated data such as Nielsen or Circana, distributor depletion reports, ERP shipment actuals) and serves up a living forecast that updates as new data arrives — reducing the burden of constant manual maintenance.

1.1 The Three Forecasting Views

The Sales Forecasting module has three interconnected tabs, each serving a distinct purpose:

Tab	What It Measures	Data Source
Consumption	Units scanned through the register — true consumer demand at the store level.	Syndicated data (e.g., Nielsen, Circana) or other POS data
Depletions	Volume moving out of distributor warehouses to retailers — a proxy for demand where POS data is unavailable.	Distributor portals (UNFI, KeHE) or depletion reports
Ship-to	Expected shipment quantities to each distributor or direct retailer. The forecast your financials and supply chain plan are based on.	SAP/ERP shipment actuals + consumption/depletion forecasts (lagged)

Note: The workflow moves left to right. Consumption and Depletion forecasts drive the Ship-to forecast. When new data arrives, users typically update Consumption, then Depletions, then gut-check the Ship-to view.

2. Establishing the Baseline Forecast

How Confido builds and maintains the steady-state forecast — exclusive of promotions and new distribution.

The baseline forecast represents the volume you would expect to sell in the absence of any promotional activity, distribution changes, or special events. It is the foundation everything else is built on top of.

2.1 How the Baseline Is Built

Confido builds the forecast at a granular driver level — down to the individual item at a specific retailer — and then rolls it up to PPG, planning group, and total customer levels. The three core drivers are:

Driver	What It Represents
Store Count	How many stores are selling (scanning) the item in a given week. Comes from syndicated data for consumption-based customers.
Base Velocity	Units per store per week, stripping out any promotional lift. This is your true baseline sell-through rate.
Seasonality Multiplier	An optional multiplier applied on top of the base velocity to account for predictable seasonal patterns. Applied per item or category.

These drivers multiply together to produce the baseline unit volume for each item at each planning group. Promotional lift is then layered on top separately (covered in Section 3).

2.2 Forecast Recommendations

One of the most powerful features of the forecasting module is the Forecast Recommendations system. Rather than requiring your team to manually monitor syndicated data reports alongside their forecast, Confido brings in the latest actuals and flags rows where the real in-store performance differs meaningfully from what you are currently forecasting.

Each recommendation tells you: here is what you are currently forecasting (e.g., 2.27 units per store per week), and here is what your latest syndicated data shows you are actually trending at (e.g., 3.96 units per store per week). Your team can then review the recommendation and accept it — which updates the year-to-go baseline — or dismiss it if business context suggests the trend is temporary.

Recommendation Thresholds

You configure what constitutes a 'medium' vs. 'high urgency' recommendation in your forecast settings. For example, a 25% variance from your current forecast might be medium, and 50%+ might be high. These thresholds can be adjusted over time as your team gets more comfortable with the system.

Tip: In steady state, the goal is for Confido to flag only a handful of rows after each new data load — maybe four items that need a look — rather than overwhelming your team with changes. During the initial setup, there will be more recommendations to clean up as data is first loaded in.

2.3 Accepting and Applying Recommendations

There are two ways to work through recommendations:

Item-level: Click into a specific item, review the recommendation, and accept it. This updates the baseline velocity for that item's year-to-go forecast.

Bulk Applying (by Planning Group, PPG): Click 'View Recommendations' at the top of the forecast. You can group by Planning Group, Product Family, etc. and apply recommendations at a bulk level.

Note: Recommendations operate at the driver level, not just total units. You might see a store count recommendation and a velocity recommendation for the same item separately. A planned store count change (e.g., you know a reset is happening in June) can be entered directly into the forecast alongside the system recommendations.

2.4 Making Direct Forecast Updates

Outside of recommendations, you can also make direct updates to any cell in the forecast. For example, if you know a store count is jumping from 2,000 to 2,500 starting the first week of June, you can click directly into that store count cell and apply the change forward — either indefinitely or for a defined period. The system may flag this as a large change, but you can dismiss the flag.

Visual trend charts are available for each driver by clicking the small chart icons on the right side of the forecast row. These show historical actuals vs. your current forecast for stores, velocity, and lift — useful for gut-checking assumptions before accepting or dismissing a recommendation.

2.5 Forecast Change Log

Every change made in the forecast is tracked. You can view a downloadable change log showing what was changed, by whom, and the impact on the year-to-go forecast. You can also compare the current forecast to a prior version — down to the driver level — to see exactly what shifted and by how much. This is particularly useful for aligning with internal IBP or S&OP cycles where forecast changes need to be communicated and documented.

2.6 Forecast Versions

Confido supports multiple forecast versions. A new version can be created at any cadence (monthly, quarterly) to represent a point-in-time snapshot. Versions can be compared side by side. This aligns with S&OP and IBP cycles where you want to lock a version, communicate it, and track how the forecast evolves from there.

Tip: Recommended workflow: Create a new forecast version at the start of each planning cycle. Use recommendations and new intel to update the active version throughout the month. At month-end, lock it and compare to the prior version for your consensus process.

3. Layering on Promotional Lift

How promotions are entered, how lift is estimated, and how it feeds back to the forecast.

Once the baseline forecast is established, promotional activity is layered on top. Promotions live in the Trade Calendar section of Confido, and their incremental volume feeds directly back into the forecast as a lift line — separate from the baseline.

3.1 Creating a Promotion

To create a promotion, navigate to the Trade Calendar and select New Promotion. The key fields are:

Planning group (retailer or distributor)
Description — use your own language or how the retailer describes it (e.g., 'TPC and Cap', 'BOGO')
In-store performance dates — when the promotion is running on shelf
Scan back days before/after — some retailers (Whole Foods, Kroger) charge scan back days outside the actual promotion window; enter these separately from the main dates
Product level — set at the PPG level in most cases, or the individual item level if rates differ significantly
Funding rate — the dollar or cents allowance you are giving to the retailer (not the retail price point)
Promoted price — the target retail price during the promotion, used for lift estimation

Note: Funding rate equals the allowance you are giving to the retailer — the actual dollars or cents per unit. If two PPGs have the same funding rate but different retail price points, you may want to put them on separate lines if you plan to use Confido's lift estimation tool, since the system uses the price point to estimate lift. If they have the same funding rate and price point, they can be on the same line.

3.2 Setting Up Multiple PPGs on One Promotion

You can include multiple PPGs on a single promotion line as long as they have the same funding rate. To add multiple products, search and select them in the product field — you can also copy and paste them. If different PPGs have different funding rates, create separate promotion lines within the same event.

Tip: Best practice: set up promo lines at the level where funding is uniform. This keeps the promotion clean for both lift estimation and deduction validation on the back end.

3.3 Estimating Promotional Lift

Confido provides several ways to estimate how incremental a promotion will be:

Historical insights: Click 'Show Insights → Historical Sales' to see a bump chart of your past promotional performance at this retailer for the selected PPG. The chart shows historical baseline volume, incremental volume, and average retail price over time. You can select past weeks where you ran a similar promotion and apply that lift percentage to the current one.
Price-based projection: Enter the target retail price for the promotion and click 'Project Lift.' Confido looks at your past promotions at similar price points and recommends an expected lift percentage.
Manual entry: You can also enter a lift percentage or exact units directly. Most teams use a percentage, which stays fixed as the baseline updates over time (so the units will change as your velocity assumptions evolve, but the percentage holds).

Note: You can also lock in exact units rather than a percentage if you want to hold a specific volume assumption regardless of how the baseline changes. Toggle between percentage and units using the toggle in the promotion entry screen.

3.4 How Lift Feeds Back to the Forecast

Once a promotion is saved, its incremental volume converts to units and appears in the 'Lift' driver line in the forecast table — for the weeks the promotion is running. The total forecast for that item in that week becomes: baseline units + lift units.

You can view just the lift units across the forecast by toggling the metric from 'Units' to 'Lift Units' in the top metrics bar. This is useful for seeing how much of your forecast volume is coming from promotional activity at any level (total retailer, PPG, or item).

Clicking into a lift cell shows which promotion is driving it, and you can navigate directly to the promotion from the forecast screen.

3.5 Lift Recommendations

In addition to baseline recommendations, Confido can surface lift recommendations in the promotion table. If you enable this setting (in Trade Settings → Show Lift Recommendations), Confido will show you where your projected lift differs from what it recommends — based on actual in-store performance at that price point. You can then review and revise your lift estimate. This is most useful after you have had several promotion cycles in the system to build history.

4. Managing Distribution Changes

How to add, remove, and track distribution — both confirmed and in-progress.

As new distribution is confirmed or lost, the forecast needs to reflect it. Confido provides two paths depending on whether the distribution is confirmed or still being worked on.

4.1 Adding Confirmed Distribution Directly

When distribution is confirmed — the retailer has committed to taking an item — you can add it directly to the forecast using the 'Add Row' function. This is for items not yet in the forecast for this retailer or items getting a meaningful expansion.

The Add Row form asks for:

Planning group and item(s)
Effective reset date — when you expect the item to start scanning on shelf
Number of stores
Expected steady-state baseline velocity (units per store per week)
Ramp-up period — the number of weeks it will take for the item to reach steady-state velocity. Confido linearly ramps the store count assumption over this period
Pipeline / pipe fill — cases per SKU per store loaded in before the reset, with an expected load-in date
Cannibalization assumptions — if this item is expected to impact the performance of other items already forecasting for this retailer (e.g., a new pack size of an existing product), you can enter a percentage impact

Tip: For items already in the forecast, the velocity field auto-populates based on your existing actuals for that retailer. For brand new items (never sold here before), you provide a manual velocity assumption.

4.2 Removing Distribution / Discontinuations

If you are losing distribution or discontinuing an item at a retailer, there are two options:

Zero out the store count directly in the forecast, applying it forward from the effective date.
Use the Discontinue button, which lets you select the item, enter the on-shelf effective date, and optionally the last order week or last ship week.

Both approaches result in the item volume going to zero in the forecast from the specified date forward.

4.3 Unconfirmed Distribution — The Opportunities Tracker

When distribution is being worked on but not yet committed, it lives in the Opportunities module — the equivalent of your R&O (Risks and Opportunities) tracker. Opportunities are separate from the baseline forecast and can be toggled on or off when viewing your numbers.

To create an opportunity, click New Opportunity and fill in:

Planning group and item
Start date (reset date) — and optionally an end date for limited-time or seasonal items
Likelihood percentage (e.g., 25%, 50%, 75%)
New stores (additional stores, not total, if the item is already in the forecast for this retailer)
Expected velocity — auto-populates if the item already exists in the forecast for this retailer
Ramp-up period and pipeline (same as confirmed distribution)
Notes — freeform field for tracking context, broker conversations, expected decision dates, etc.

Note: Custom attributes (tags) can be added to opportunities for additional categorization — for example, tagging opportunities to specific OKRs, strategic priorities, or opportunity tiers. These can be set up at any time in settings and do not need to be defined upfront.

4.4 Viewing Opportunities in the Forecast

When viewing the forecast, you can configure which opportunities to include using the 'Configure Opportunities' button. Options include:

Include all opportunities, weighted by their likelihood percentage
Include all opportunities at full volume (as if 100% likely)
Include only opportunities above a certain likelihood threshold (e.g., 75%+)
Exclude all opportunities from the view

This is a view-level setting — it does not change any saved data, and each person can configure their view independently. Weeks where opportunity volume is included are highlighted in the forecast table for easy identification.

4.5 Confirming or Canceling an Opportunity

When you receive word from a retailer on a committed opportunity:

Confirm: Click the confirm action on the opportunity. This moves the volume from an outlined opportunity into the baseline forecast assumptions (store counts update, etc.). The opportunity becomes part of the confirmed forecast.
Edit then confirm: If the retailer accepted but with different details (e.g., 400 stores instead of 200), click edit to update the assumptions, then confirm.
Cancel: If the opportunity did not come through, cancel it. Canceled opportunities are archived and always visible in the history filter — you can always go back and see what opportunities existed and what happened to them.

5. Growth Factors

A dedicated multiplier layer for modelling expected velocity growth or decline — separate from promotions and distribution changes.

Growth factors are a distinct driver layer in the Sales Forecasting module, separate from promotions, opportunities, and distribution changes. They are used when you have an expectation that your everyday baseline velocity will change over a period of time — not because of a specific promotional activity, but because of something broader such as a marketing investment, double placement, brand momentum, or household awareness growth.

Note: Growth factors are not entered in the forecast table itself. They live in a dedicated Growth Factor section of the Sales module and feed into the forecast as a multiplier row alongside the other drivers.

5.1 When to Use Growth Factors

Common use cases include:

Double placement: You know your product will have two shelf locations (e.g., in-aisle and at the register) for a fixed number of weeks, and you expect a 50% velocity increase during that period — but it is not a funded promotion.
Marketing investment: Your team is increasing media spend or digital investment at a specific retailer or across a product line, and you expect that to translate into a 20% velocity lift by year-end.
Brand/category momentum: Your AOP includes an expectation of organic velocity growth — for example, 10% brand momentum applied broadly across your forecast as part of your annual building blocks.
Targeted velocity growth: You are investing heavily in one specific product line and want to model a velocity ramp-up without changing every individual cell in the forecast table.

Tip: Growth factors are most useful when you want the multiplier to be visible and tracked as its own driver, separate from your base velocity assumptions. If you only need a one-time adjustment, editing the velocity cell directly may be simpler. If it is a broader assumption you want explicitly called out, use a growth factor.

5.2 How to Create a Growth Factor

Navigate to Sales → Growth Factor section. Click New Growth Factor and fill in:

Name — a descriptive label (e.g., 'Blueberry Bars Marketing Investment', 'Total US Brand Momentum Q3')
Product scope — you can apply the growth factor at any level: total brand (leave product blank), product family/PPG, or individual item
Customer scope — you can apply it to all customers, a specific channel or attribute (e.g., US vs. Canada), or individual retailers. Leaving it blank applies it to all customers globally, including both US and Canada
Date range — the start and end of the period during which the multiplier applies
Growth type — Overlay or Scaled Overlay (see below)
Growth percentage — the multiplier amount

Once created, Confido previews the volume impact before you confirm — showing you the before/after on a weekly basis so you can validate the effect.

5.3 Overlay vs. Scaled Overlay

Type	How It Works	Best For
Overlay	Applies the same percentage multiplier to every week in the date range. A 100% overlay doubles velocity every week for the full period.	Point-in-time boosts where the full impact is felt immediately — e.g., double placement for 6 weeks, a confirmed in-store event.
Scaled Overlay	Ramps up gradually to the target percentage by the end of the date range. A 20% scaled overlay starts near 0% and builds to 20% by the final week.	Gradual growth assumptions — e.g., brand awareness building over a year, marketing investment with a ramp-up period, AOP momentum assumptions.

5.4 Growth Factors and Forecast Recommendations

An important interaction to be aware of: if a growth factor is applied and consumption actuals also start trending up (captured in syndicated data), Confido's recommendation system will flag the velocity increase. At that point, you have a choice:

Accept the recommendation and remove the growth factor — effectively locking in the growth as a new baseline velocity, removing the explicit multiplier.
Dismiss the recommendation and keep the growth factor — allowing it to continue building if you believe there is more growth still to come.

This interaction means growth factors work well at the beginning of a planning cycle, when you have an expectation of future growth that actuals have not yet confirmed. As the year progresses and actuals catch up, you can decide whether to absorb the growth into the baseline or continue applying the explicit multiplier.

Tip: To avoid double-counting: if you accept a recommendation that already reflects the growth you had modeled in a growth factor, remove the growth factor at the same time. Otherwise you will be applying the growth twice — once in the velocity baseline and once as a multiplier.

5.5 Managing Growth Factors

All active growth factors are visible in the Growth Factor section, where you can review, edit, or roll back any of them. Rolling back a growth factor removes the multiplier from the forecast and restores it to the underlying baseline. Confido will show you the volume impact of the rollback before you confirm.

Permissions note: Because growth factors can have a broad impact across the forecast — especially if applied at the total brand or total customer level — it is common to restrict which users can create and edit them. Your Confido onboarding team can configure role-based permissions so that only specific users (e.g., finance or planning leads) have access to this section.

6. Planning Shippers and Displays

How to plan display and shipper activities in the Opportunities module.

Shippers and display activities are planned within a dedicated Shipper/Display tab in the Opportunities module. This is where you track all upcoming shipper load-ins, their timing, the number of stores, and whether the volume is incremental to your everyday baseline.

6.1 Creating a Shipper or Display Opportunity

Toggle to the Shipper/Display tab within Opportunities and select New Opportunity. The key fields are:

Retailer (planning group)
Shipper product — select from the configured shipper/display kits in the system (the full kit or build, not individual scan units)
Confirmed toggle — if the retailer has already committed to taking it, toggle to confirmed; otherwise assign a likelihood percentage
Number of stores and quantity per store (e.g., 200 stores, 1 shipper per store)
Load-in date — the exact date you plan to ship the shippers to the retailer
In-store performance dates — when you expect the shippers to be on the floor selling
Notes

Note: If you have two different shipper configurations for the same opportunity, create two separate shipper opportunities — one per kit.

6.2 Incremental vs. Non-Incremental Shippers

One of the more nuanced settings is whether the shipper is 'fully incremental' to your everyday forecast.

Fully incremental: The shipper volume is completely additive. The retailer loads the shippers AND continues to order the underlying master cases at the normal rate. The load-in quantity represents pure upside volume.
Not fully incremental: The shipper load-in effectively front-loads product that the retailer would have otherwise ordered through normal replenishment. This means their regular master case orders will slow temporarily as they work through the shipper inventory. You can enter a lift assumption to model how incremental the shipper volume actually is.

Tip: For teams just getting started with Confido, start by treating shippers as fully incremental and entering the total load-in volume. As your planning process matures, you can add incrementality assumptions to get more precise.

6.3 How Shippers Appear in the Forecast

On the Ship-to side of the forecast, the shipper item itself appears with its planned load-in quantity on the specified date. The underlying sellable items (the individual scan units inside the shipper) continue to appear in the Consumption forecast as normal — what you are planning in the shipper module is the warehouse-level load-in of the physical shipper units, not the consumer scan activity.

7. Depletions Forecasting

For retailers where you have distributor pull-through data instead of POS/syndicated data.

For some retailers — particularly those that sell through distributors like UNFI or KeHE, or smaller regional accounts — you may not have syndicated data. In these cases, Confido uses distributor depletion data (how much volume the distributor shipped to those retailers) as a proxy for demand.

7.1 When to Use Depletions vs. Consumption

Use the Depletions tab for retailers where:

No syndicated POS data is available (common for specialty, natural, co-op, and foodservice accounts)
The retailer orders through a distributor and you receive depletion reports from UNFI, KeHE, or similar
You want to forecast for a group of smaller independent accounts that pull through a single distributor

Each planning group is set up as either consumption-based or depletion-based — not both. Which methodology feeds the Ship-to forecast depends on this setting per planning group.

7.2 How Depletions Forecasting Works

The Depletions tab operates almost identically to the Consumption tab — the same drivers (store counts, base velocity, lift), the same recommendations system, the same visual charts. The key differences are:

Actuals source: Instead of syndicated scan data, actuals come from distributor depletion reports (UNFI portal, KeHE portal, or uploaded CSV reports).
Data frequency: Consumption data is typically weekly. Depletions data from some distributors may come monthly or even quarterly — Confido will straight-line this into weekly buckets during upload.
Store counts: 'Stores' in depletions means the number of retailer locations that ordered product through the distributor in a given period. This is pulled from the distributor data directly — though you can also adjust the forecast forward based on new intel (e.g., you know 100 new independents have started ordering).
Seasonality: Can be added to depletions forecasting, though teams often keep depletions simpler than consumption.

Note: Recommendations, visual charts, and the ability to accept or dismiss suggestions all work the same in the Depletions tab as they do in Consumption. If your depletions data is inconsistent or aggregated, it may be worth using a simpler approach (e.g., manually entering a monthly velocity estimate rather than relying heavily on recommendations).

8. The Ship-to Forecast

How consumption and depletion forecasts translate into shipment-level volume.

The Ship-to forecast is where everything comes together. It represents the expected shipment quantities to each physical ship-to customer (a distributor, retailer DC, or direct retailer) — the numbers your financials, supply chain, and production planning are built on.

8.1 How the Ship-to Forecast Is Built

The Ship-to forecast is driven by the Consumption and Depletion forecasts, lagged by a 'buy-in delay' that represents how many weeks before consumption you expect to actually ship the product.

For example: if your buy-in delay for Target is two weeks, and you forecast 185,000 units consumed in the week of May 23rd, you will see those units appearing in the Ship-to forecast for the week of May 9th — two weeks earlier.

The ship-to actuals come from your ERP (SAP or equivalent) — so you see real historical shipment quantities alongside the forecasted values, all in one view.

8.2 Consumption vs. Ship-to: Understanding the Difference

Important: The Consumption and Ship-to views will show different numbers — this is expected and correct. Consumption actuals come from syndicated data (what scanned through the register). Ship-to actuals come from your ERP (what you physically shipped). They are different data sources measuring different points in the supply chain.

When you see different numbers between the two tabs, it does not mean there is an error. It reflects the normal lag between shipment and consumer purchase.

8.3 Recommended Filters

On the Consumption tab: filter using the Planning Group field (e.g., 'Target', 'Whole Foods').
On the Ship-to tab: filter using the Customer field (e.g., 'UNFI', 'KeHE', 'Target DC'). This is the physical ship-to entity, not the end retailer.

Tip: For retailers like Target where you ship direct, the Planning Group and Customer may be the same. For retailers served by a distributor, your Ship-to customer will be the distributor (e.g., UNFI), and the planning group would be the individual retailer pulling through UNFI.

8.4 Direct Shipment Forecasting

For customers where you have no consumption or depletions data — smaller distributors, tier-three customers, or accounts where you simply want to forecast directly at the shipment level — Confido supports Direct Shipment forecasting.

For these customers, you bypass the Consumption and Depletions tabs entirely and forecast directly in the Ship-to tab. The view is simpler: historical shipment actuals from your ERP alongside open cells where you enter total forecasted units (or cases, or dollars) for each item, each week.

This is an all-encompassing volume entry — both base and promotional volume combined in a single cell, since there is no separate consumption or lift driver structure for direct shipment customers.

8.5 Viewing and Editing Units, Cases, and Dollars

The Ship-to forecast can be viewed and edited in units, cases, or dollars. Editing is done in units or cases; the dollar view is for context. The forecast can also be grouped by periods, quarters, or the full year — using your company's specific fiscal calendar (e.g., a 4-4-5 calendar if configured).

Sync to Data Store: If your company uses a data pipeline that feeds forecast data to an external system (e.g., Google Sheets, Datasphere), the 'Sync to Data Store' button triggers a refresh of that feed with the latest forecast data.

9. Frequently Asked Questions

Common questions from training sessions and onboarding calls.

Q: Can I update the forecast at the PPG level rather than item by item?

A: You can view and bulk-apply recommendations at the PPG level using the 'View Recommendations' flow at the top of the forecast — filter to a planning group and group by PPG to see the combined impact and make bulk changes. The underlying forecast table itself operates at the item level, but recommendations provide a PPG-level workflow. You can also use the Bulk Update function to change store counts across a filter set all at once.

Q: How does seasonality work? We have a business that peaks in summer — will recommendations over-call winter volume?

A: You have two options. One: accept recommendations only through a certain date (e.g., through August) and manually hold your seasonality-adjusted assumptions for the rest of the year. Two: set up a seasonality multiplier in Confido settings, which gets stripped out of the recommendations logic so that the system compares apples to apples when flagging changes. The seasonality multiplier is then applied on top of the baseline. The second approach is more sophisticated but provides cleaner automation.

Q: Is there a change log to see what was updated in the forecast?

A: Yes. The change log tracks every change made — what was changed, by whom, and the impact on year-to-go volume. It is downloadable. You can also compare any two forecast versions side by side at the driver level to see what shifted between them. Both tools are useful for aligning on forecast changes in S&OP or IBP cycles.

Q: Can Confido recommend a ramp-up period for new distribution?

A: Not automatically today. When you add new distribution (either confirmed or as an opportunity), you manually enter the ramp-up assumption based on your own experience with that retailer. This is a roadmap item — longer term, Confido aims to use cross-brand benchmarks to suggest typical ramp periods by retailer.

Q: When an opportunity is confirmed, does it automatically update the forecast? And what happens to linked promotions?

A: When you click Confirm on an opportunity, the volume gets baked into the baseline forecast assumptions (store counts update). If you set up a linked promotion (e.g., a slotting fee associated with the distribution), that promotion is already in the trade calendar and is not removed — it continues to exist as a planned event. You can configure whether opportunity volume above a certain likelihood threshold should flow through trade promotions as base volume.

Q: What is the difference between the planning group filter (Consumption tab) and the customer filter (Ship-to tab)?

A: Use planning group when filtering on the Consumption or Depletions tabs — this is the end retailer (e.g., Whole Foods, Target). Use customer when filtering on the Ship-to tab — this is the entity you are physically shipping to (e.g., UNFI, KeHE, Target DC). For direct-ship retailers, these are often the same entity.

Q: Can promotions affect whether opportunity volume flows through trade?

A: Yes, this is configurable. If you include opportunities above a certain likelihood threshold in your forecast, that volume flows into the base units on corresponding promotions. You can also create a directly linked promotion for an opportunity (e.g., a slotting fee) right within the opportunity creation form. Talk to your Confido onboarding team about how to configure opportunity-to-trade flow for your business.

Q: What does 'Sync to Data Store' do?

A: If your organization has set up a data pipeline that feeds Confido forecast data out to another system (e.g., Google Sheets, Snowflake, Datasphere), clicking Sync to Data Store triggers an on-demand refresh of that data feed with the latest forecast values. It is not needed for normal forecast management — only for brands that have configured an external data connection.

Confido Sales Forecasting Module — Internal Reference

For questions, contact your Confido onboarding team.

Sales Forecasting Module - How it Works