If your marketing and buying teams are not sharing data and plans frequently you are likely missing out on sales. In this article we’ll explain why a tight collaboration is crucial for any D2C brand in order to increase performance.
Two of the biggest costs on a D2C brand’s P&L is typically cost of goods and marketing spend/customer acquisition. Essentially, supply and demand (generation). There is a lot more that most brands can do to synchronize these two sides of the equation, so that they work in better harmony.
Marketing departments typically optimize for metrics such as ROAS (return on ad spend) while buying teams focus on e.g. sell-through or gross margin. The risk of isolated KPIs is isolated behavior, but marketing and buying/merchandizing hugely impact each other. Sharing processes and information in a more structured manner opens up opportunities for higher performance on overarching metrics: sales and bottom-line profits. A couple of examples:
- Brands typically need to make purchase orders from production way ahead of the selling period, meaning demand forecasts need to stretch over a long time. Planned campaigns, marketing spend and pricing are some of the most important factors for future demand. Whatever is known well ahead of time with regards to these factors, should be factored in to demand forecasting and buying
- Long-term demand forecasting is hard, and for sure not all articles will sell according to plan. Parts of the assortment will need help from demand generating activation so that the brand don’t end up with large overstock at end of season - which is killing margins and brand perception. Other articles will sell better than plan, meaning they don’t need help at all. This is very important information for a marketing team. Spend should focus on where it is needed, and if products will sell out anyways over the sales cycle and re-stock can’t make it in time, it is a lot better to take home the profits
So, our solution to this is a three step approach:
- Set pre-season/long-term sales plans for each individual article, with the best available information at hand, including known marketing initiatives. These then function as a baseline, and if everything (pretty much) follow the baseline it would mean operations will run smoothly
- When the articles start to sell, follow up on early signals on how they are trending versus the baseline. The initial sales data can feed into re-forecasting, and the calibrated outlook feed into what needs to be done. With a large amount of articles and a lot of other things to think of, software support to automate read & react typically helps
- Take action based on the outlook. Feed marketing with information about what articles need help to catch up with the desired curve, and what articles are selling well as it is. This can help ensure marketing money is being spent wisely
The outcome is higher bottom-line profits, less overstock for end of season clearance, and overall smoother operations and fewer hiccups in supply chain.
Madden Analytics recently had a webinar together with marketing agency Keywordio on this topic. The full webinar available here
And, Madden Analytics has the right solutions to support this work - book a demo here to learn more.
