Fighting High Inflation with Customer Analytics

As we’re all painfully aware, elevated inflation is top of mind universally for most consumers. 
16 May 2022
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Vidyut Vashi

Partner, Analytics Practice

It has been a source of discomfort among buyers across all consumption categories, ranging from everyday food items at the grocery store to used cars, and everything in between. But there are fast analytics strategies businesses can use now to combat adverse effects of high inflation.

It is important to recognize that neither consumers nor corporations have experienced the recent soaring rates of inflation in several decades. Such unprecedented times call for a rethinking of past and current strategies to combat changing consumer behaviors. While consumers typically and expectedly adjust their consumption behaviors during such times due to a strain on their budgets, it is important for sellers (corporations) to adjust their strategies as well to mitigate the negative impact of inflation.

There is consensus that rising inflation needs to be addressed by either keeping it in check or preferably bringing it down from current levels. While government policies can certainly play a role in controlling inflation, it would be prudent for corporations to take proactive actions to mitigate the negative effects of inflation on consumers’ budgets and pocketbooks.
"Consumer concerns are echoed by business leaders. A Conference Board survey of Global CEOs conducted during October and November 2021 found 55 percent expecting higher prices through mid-2023 and beyond. Inflation was number two in their list of external threats to business, up from number 22 the year before. Inflation is just as unfamiliar to businesses as it is to consumers. Less than 40 percent of the CEOs in the Conference Board survey said that their companies are “well prepared” for an inflationary marketplace." J Walker Smith, Chief Knowledge Officer, Kantar: Inflation and Risk Reduction

Some of the strategies and tactics of the past, such as relying on historically developed elasticity metrics or assuming uniform demand, are found to be ineffective in current market and economic conditions.  

While receiving, reviewing, and reading both external reports and syndicated data are helpful in getting a broader understanding of the inflationary pressures in the marketplace, such reports often fall short on specific actions at the customer level. Firms that capture their customers’ behavioral and attitudinal data are at an advantage in terms of their ability to act with defensive and/or preemptive measures to fend off high inflation’s negative effects on their customers.

We believe that corporations must take advantage of their readily available customer data. Mining and analysing internal customer purchase and transaction data, panel data, survey data in addition to syndicated data will provide valuable insights and knowledge to decision makers.  
The following analytics strategies can be used now to combat adverse effects of high inflation: 

Demand Estimation and Forecasting activity is commonly undertaken within almost all professionally managed corporations of all sizes. Demand estimation attempts to quantify the links between the level of demand (sales) and the variables (factors) that influence it. Forecasting, on the other hand, attempts to predict the overall level of future demand rather than looking for specific linkages. 
Given that the current inflationary economic environment will be negatively impacting the demand for products and services, pricing managers are advised to pay closer attention to factors affecting demand for their goods. They need to incorporate external variables such as income and employment levels, CPI levels, etc. to accurately estimate and forecast demand. Adjusting previous forecasts to accommodate current macroeconomic reality would benefit the planners. More advanced techniques such as ARIMAX and Cross-Sectional Time Series modeling can improve the model accuracy and reduce error rates. The ability to incorporate and update information in real time is strongly recommended.    
Cross-selling is the action or practice of selling additional products or services to an existing customer. In practice, businesses define cross-selling in many ways. 

One of the objectives of cross-selling during the current economic environment of high inflation is to protect the relationship with the customer. However, it is important to bear in mind that the additional product or service being sold to the customer enhances the value the customer gets from the seller. 

One recommendation is to adopt the Bundling strategy. This strategy entails (a) bundling or prepackaging related products, so the customer doesn’t need to look for necessary components or accessories, and (b) offering a discounted price on a bundled product offer to encourage immediate purchase with a temporary price savings. Mining the already available customer purchase data makes this approach feasible in an expeditious manner.  

Moreover, ML/statistical predictive modeling can be deployed on data made available from current customers to identify prospects for cross-selling and develop effective and profitable cross-selling strategies. A targeted marketing campaign for those customers who are more likely to respond to a bundled offer is an efficient use of marketing dollars.       
Basket Analysis, simply put, is looking for combinations of items that occur together frequently in transactions to uncover associations between items. The goal of Basket Analysis is to analyse relationships between items that people buy.  
During these inflationary times, consumers tend to adjust their basket due to increase in prices as well as operate under the constraints of the budget. They tend to either (a) buy less of the same (reduce the quantity), (b) delay their purchase, (c) buy substitutes (e.g., brand switching), or (d) trade down (opt for private labels). A detailed Basket Analysis of customer purchase data, encompassing longitudinal view, will help gather insights into the changing behaviors over pre-inflationary time-periods. Such knowledge will equip the decision makers with strategies to counter unfavourable behaviours. 
Segmentation and Personalisation are two strategies that, when implemented and executed effectively, will support the brand to combat inflation.  
Dividing the customer base on their behaviors and attitudes enables the sellers to identify cohorts that exhibit similar behaviors and attitudes, e.g., price conscious segment, and price agnostic-quality conscious segment. Such insight will allow the client to manage promotions and customer specific communications to particular segments. Meeting the needs of these cohorts with appropriate pricing and promotion messaging is a clever way to mitigate the ill-effects of price increases.  
Personalisation is the art and science of tailoring the right message to the right customer at the right time via the right channel of communication. While segmentation identifies homogeneous cohorts for devising broad marketing and communication strategies, personalisation can further enhance and customise these strategies at the individual customer level. By analysing customers’ purchase activity, transaction details, messaging and communication channel preferences, firms can customise a personal message and offer. Such personalisation, when offered in a timely manner, can preserve the customer relationship during tougher economic times and further strengthen the relationship, build loyalty in the future.   
Customer Surveys are beneficial in capturing the attitude and preferences of consumers. It enables the seller to get reactions and impressions of the consumer on an ongoing basis. It captures what is on the consumers’ mind, addressing the proverbial “why”. By analysing such feedback, the seller can adjust their pricing strategy as well as customers’ experience with the seller’s product and services.  
By cleverly crafting the survey questions, the seller can develop improved and innovative products that offer better value to mitigate the negative impact of price increase due to the current economic environment.  Moreover, by combining the survey and panel data with transaction data, firms can devise and deploy marketing promotion strategies that are more meaningful to the customers. 
Opportunity Sizing and Scenario Planning is a method that many successful organisations use to make flexible long-term plans. The method combines known external facts, such as current macro-economic information, supply chain constraints and industry syndicated data (for competitor intelligence), with internal facts, such as production capacity, labor constraints and production innovation pipeline, to generate simulation games for corporate strategists and planners. It will help management develop an understanding of the possible scenario outcomes in the future and their impact on the business. It allows the client to create profitable growth scenarios that allow for flexibility in a fluid and rapidly changing environment. 
Successful organisations perform scenario planning exercises on a regular frequency to accommodate the ever-changing business environment and consumer sentiment. Often there is more than one scenario under consideration and corresponding financial models are built accordingly. In the current inflationary environment, the impact of an increase in the prices needs to be analysed not just at the entire customer base level but also at a more granular level (e.g., segment and sub-segment levels.)     
Kantar’s Customer Analytics team of seasoned analytics professionals can help dig deeper with one or more of the above analytics approaches to battle high inflation. Our experienced analysts and consultants can work side-by-side with your teams to develop profitable customer strategies to successfully navigate through a challenging economic environment.  

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