Sales has always been about numbers; you either sell, or you don't. This, in turn, makes sales people keen analysts of their environment. They also place great emphasis on the sales process, salesmanship, and training.
But, these days, that may not be enough. New technologies, tools and techniques exist that can make sales people's jobs easier and more productive.
For example, sales people now use handheld devices to take orders. So, sales persons with multiple SKUs can now predict which stores will buy a new SKU, or where a new SKU can be cross-sold. Consequently, the sales team can focus on fewer stores with a better chance of conversion.
Similarly, sales across geographies can be tracked at a micro or macro level. This data can then be compared with the purchase of other durables or lifestyle variables. As a result, the sales team can increase market penetration by focusing on the right areas, while optimizing sales people's time and effectiveness.
Analytics also tracks sales people's efficiency better than traditional methods. As markets differ, going by numbers alone could result in a less efficient person in an easier market getting rewarded ahead of someone better, but in a more difficult territory. Instead, models that bring in the other factors lead to a fairer and more efficient system.
From a B2B perspective, analytics avoids the traditional 'spray and pray' approach of engaging different potential customers with a variety of products. Instead, based on past data and on other characteristics, models can be built to accurately predict which products can be sold to whom, and when.
Is there a right and royal RoAS?
Written by :
Krishna Kumar CS
RoAS - the single most powerful metric known to advertisers. It can enrich or ruin your ad campaign. It can make or break your brand. It is an essential ingredient to optimise your Ad spend. According to some, it is the holy grail of marketing.
Why Attribution is passé, even for online marketers
Written by :
For some years now, Attribution analysis has been king, and digital is being measured using Attribution models, which evolved over a period of time from simple attribution to the website of the transaction, to giving some credit to the others in the funnel (judgemental); and finally, to some statistical methods used to weight the impact of each website along the purchase path. Despite all of these advances, Attribution always suffered from a fatal flaw of not taking mass media, in store activity and promotion or indeed brand equity into account. This meant that all credit was given to advertising online, and the credit duly inflated. Not the ideal situation for your brand.
Data science offers a more precise guide – computing the price elasticity at a key SKU level can suddenly make this exercise a lot easier. While we still use judgement and intuition, now our gut is better informed and therefore the decisions are much better as they are based on hard data.