Aperity’s approach on forecasting leverages analytics found in both banking and metallurgy. We combine multiple forecasting methods to produced the best fit possible. At report execution, we compare the results against historic trends to ensure the forecast is accurate.
Ease of Use – Forecasts are built from the store level up. Users simply ask for the geography and brands and the forecasts are delivered back in both grid and interactive graphs. Add to a dashboard and the output becomes an incredible tool for sales and marketing.
Granular – Our models are applied to over 500,000 stores weekly. Stores are analyzed across your entire portfolio for movement across all brand levels and sizes. Look at entire markets or drill to an individual store for analysis. Target stores directly from the report output.
Flexibility – We build the forecasts live within the database. There is no need to export the data to another tool and then find out it wasn't what you exactly wanted. Because forecasts are build from the most granular data, we can forecast on any combination of product and geography attributes. Coupled with TDLinx, there's an endless supply of forecasts that we can generate.
What are the likely stores that will respond well to your promotion? What type of promotion should I run in a set of stores? We take historical store sales and match them up with past promotions to provide a prediction on what will happen in the future. We also look for other stores that would be good candidates for your brand. This can be improving brand performance in existing stores or find new distribution opportunities for your brand.
The more information you have on what you did in stores, the better the simulation. We have channel partners that provide the right tools for collecting in store activities and we integrate that with our store information – sales, channel information, local demographic data, and other factors to build a simulation model.
Ease of Use – Identify a brand and a set of stores. We can simulate the performance of the promotion in the set of stores. Identify a store, custom group of stores, or entire markets.
Granular – Our models are applied to over 500,000 stores. Stores are analyzed across your entire portfolio. Look at entire markets or drill to an individual store for analysis. Target stores directly from the report output.
Flexibility – Not all brands are alike, nor should they be measured the same. Aperity adjusts the model based on the brand.
What happens when your competitor drops their price? What impact does that have on your sales? How do your other Trade Marketing activities impact your other brands? Price changes within your portfolio can have dramatic cross brand influences. We analyze how your brand is correlated within your portfolio and competitors. Just like our other modules, change your questions on the fly to understand how different markets act. Our analysis is done straight from your transactional data through the supply chain. Analyze individual stores, chains, markets, or distribution channels on the fly.
Ease of Use – Simple prompts guide you through the process. Change brands, time periods, and markets for analysis that fits your needs. Make pricing What If adjustments to identify the right mix of profit and volume.
Granular – Analyze to the depth that you need. Look at complete brands or portions of your brand. Look certain markets, chains, distributors, channels or individual stores. Because we perform the analysis within the database, change the scenario based on your needs. Look at entire markets or drill to an individual store for analysis. Target stores directly from the report output.
Flexibility – Dynamically adjust what markets are being analyzed on the fly. Aperity automatically recalculates the opportunity on the fly.