INDIA/INTERNATIONAL. Voiceback Analytics has developed custom processes for brands operating in travel retail which it claims can boost operating margin and profitability. By using depletion data the company says it can identify the best SKUs for promotions.
Led by former Flemingo Travel Retail CEO Manishi Sanwal, the Bangalore-based start-up believes that while promotions are commonplace in travel retail, they are often under-analysed and based on judgement calls or intuition.
“Promotions are planned by category buyers or by brands mostly looking at their inventories or sell-out targets and/or historical experience. But it is difficult to determine whether a promotion plan is the most relevant or that it will generate the highest sales response,” said Sanwal.
Voiceback Analytics uses predictive analytics to optimise the cost of a promotion by identifying which SKUs should be promoted and which should not, perhaps because they may not respond to discounts or promotions.
With duty free stores often running multiple promotions simultaneously, Sanwal believes that a data-driven approach can yield a better outcome for passengers, retailers and brands.
“Finalising a promotional plan for a big brand with multiple SKUs is complicated and has a direct impact on business profitability. We are trying to create a scientific structure to determine a better model for planning these promotions,” Sanwal said.
Deep dive into depletion sales data
All major travel retailers share depletion sales data with brands on a monthly basis. This data – which includes past month sales quantities and net sales value in US dollars – can be used to ascertain the level of promotional discounting.
“We use historical sales data and analyse it to provide a guide for future activity,” said Sanwal. “Such a study can be done for retailers/operators as well as for the brands to improve their promotional offer and their profitability.”
Within the historical data, Voiceback Analytics looks for two statistical indicators: the correlation between price and volume (which reveals the impact of price discounts on volumes sold); and residual variance (other factors that affect business volume such as growth trends, seasonality or competitive activity at destination airports).
By using time-series algorithms the company claims it can determine the impact caused by tactical activities of any kind. By reviewing both indicators brands can act more confidently by, for example, offering deeper discounts on those lines identified as responding better to promotions; reducing discounts on brands which don’t respond, or focus on softer improvements like shelf space optimization and staff incentives instead.
In a travel retail case study, Voiceback Analytics said that by using its model, promotion budgets as a percentage of sales came down which led to a direct increase in operating margins without affecting sales trajectory.