Banks and other financial institutions use predictive analytics to ascertain the track record of its customers in loan repayment before disbursing further credit to them. Travel agencies use predictive analytics to identify peak travel seasons and devise their marketing strategies to tap the expected surge in demand. There are hosts of other industries which bank upon predictive analytics to gain marketing leverage.
Given what present day predictive analytics can deliver in terms of actionable marketing information, retail honchos have started making extensive use of predictive analytics in their retail management and are reaping the primary and downstream benefits stemming from it.
1. Understanding consumer behaviour
Consumer behaviour is amazingly predictable. It can be mapped and behavioural patterns can be established. This information can further be utilized towards enhancing customer satisfaction, improving customer service and enriching overall customer experience.
The key requirement towards understanding consumer behaviour is having quantified data on actual consumer activities. These include data on quantity and frequency of purchases, frequency and duration of visits, areas of purchases, price sensitivity, response to promotional activities etc.
Predictive analytics, by means of advanced statistical software tools, processes these quantified data on consumer behavioural activities to forecast future buying behaviour of consumers.
Online shopping portals use predictive analytics to highlight and promote products and services based on customers’ past purchases and recent searches. Various social media platforms use complex algorithms (as part of predictive analytics) to present to its users relevant content.
2. Tuning the marketing mix
Product selection and development – Based on analysis of past patterns and forecasts of future consumer behaviour, Predictive Analytics helps retailers better understand the needs and wants of their customers. Such information is vital for development of existing and new products. Retailers could get to know which products they should focus on and which ones to be discarded off the shelf.
Price sensitivity – There are various approaches towards pricing of a product or service. Predictive Analytics provides the necessary statistical information and price sensitivity analysis as a guiding force in the pricing process. Price sensitivity plays a pivotal role in product pricing. Movie theatres use predictive analytics to adjust the prices of its tickets to attract movie goers on the weekdays.
Promotional campaigns – Having the forecasts of buying or non-buying behaviour of customers, retailers can put in place suitable promotional campaigns, customised offers, discounts etc.
Sales and marketing staff – As predictive analytics help retailers plan ther marketing strategies in advance, it also puts them in a position to allocate required manpower according to those predetermined strategies. It is broadly discussed later.
Distribution and delivery – Retailers also use predictive analytics to decide upon the channels of distribution and mediums of delivery for different products and services based on geographical concentration of customers. Such decision making would get complicated without a location based analysis of the past trends and forecasts of sales.
3. Supply Chain Management
Typical supply chain activities involve placing orders, procurement, storage, despatch, audit and control, reorder and the cycle goes on.
In order to maintain steady and necessary levels of stock all the time, retailers need to plan and prepare its supply chain strategies in advance on a perpetual basis.
In today’s retail environment, such decision making has been made convenient with the use of modern age software and technologies like predictive analytics. Because there’s a holding cost involved and timely delivery of orders is of utmost importance to customer satisfaction and customer retention, retailers need accurate statistical analyses and forecasts to rely upon in making supply chain decisions. In this pursuit, predictive analytics has become one of the indispensable tools in supply chain management.
4. Risk Minimization
Retailers, irrespective of the industry they are into, face several risks ranging from demographic shifts in the areas of operation to changes in customer preferences, from shortages in supply to seasonal fall in demand, from rise in competition to poaching of employees and so on.
Predictive analytics help retailers statistically forecast such disturbances in the external and internal environment of a retail enterprise thereby enabling them to make the necessary changes in their marketing strategies.
5. HR empowerment
HR empowerment is one of the downstream benefits of predictive analytics for a retail enterprise. Once the marketing goals and strategies are finalized, retailers find themselves in a position to take calls on manpower requirements to roll out the marketing activities.
After job analysis is done, recruitment drives can be initiated and suitable candidates could be hired before the competitors does.
Recruitment is a costly and time consuming process. If the firm knows what skills and attributes they want in retail staff, existing staff could be imparted short term training and development programs.
It is never easy to be a front line retail staff doing the same things every day. Right from appearing presentable to striving to get a purchase finalized, it can get too tedious a process to be routine. Various financial and non-financial incentives could be attached to the pay structure of retail staff.
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Chief Strategy Officer