Sunday, Nov 28

Competitive Pricing Using PromotionsThe analytics opportunity

Competitive Pricing Using PromotionsThe analytics opportunity

Nicked named the 4 P's of marketing, Price, Product, Place, and Promotion have been identified as the four pillars of a successful marketing strategy, which when properly combined, could get the product or service to the right audience at the right time. However, coordinating these key ingredients, often referred to as the Marketing Mix, is one of the teething troubles of most marketers and retail businesses since time immemorial. 

Recently, increasing competition driven by globalization, digitization, and increasing taste for entrepreneurship, makes it very important for businesses to coherently blend the 4 P’s to remain competitive; serving the needs of their customers. Even more complicated for most businesses, especially retailers, is how to combine promotions with pricing that will not eat into the profit margins of the organization.

A recent McKinsey research shows that many retailers underestimate the value of coordinating decisions on pricing and promotions. Such uncoordinated and counterproductive decisions happen much more often than most retailers realize, and they are expensive. In some cases, promotions don’t turn a profit at all, or at least they don’t add nearly as much profitable revenue as retailers expect.

Addressing this 50 TVM Competitive Pricing Using PromotionsThe analytics opportunity conflict can quickly turn into a game of cat and mouse, in which retailers find themselves constantly chasing the next issue in a highly reactive way. Sometimes they simply avoid the problem by keeping prices low or making small adjustments across the board, in effect, creating a permanent discount on their entire assortment. 

PRICING AND PROMOTIONS ANALYTICS

Luckily, research has shown that with better analytics, e-commerce retailers can create value by intelligently linking pricing and promotions based on optimal price setting and promotion design.

For instance, McKinsey found in its research that several innovative e-commerce retailers increase revenue and profits by three to five percentage points using a highly differentiated analytics process and often achieve improved customer satisfaction and loyalty as well. The analytic process involves three main steps that can help retailers or marketers in general increase sales whilst achieving customer satisfaction.

DETERMINING PRICE SENSITIVITY FACTORS

The first thing to do in the analytics is to determine the factors to include in the price sensitivity analyses. For a better understanding, a price-sensitivity score considers the extent to which customers perceive a product’s price and, as a result, react to price changes. If a product has a higher price-sensitivity score, it means that a customer is less likely to accept a price increase. In this case, the price should be kept at a competitive level.

However, most businesses use only a small number of variables to determine the price-sensitivity score. “While most companies consider price sensitivity when they make pricing decisions, the scores often don’t incorporate enough factors and thus aren’t as accurate as they could be. The best price-sensitivity scores are calculated with advanced analytics, using input factors that take customer, competitor, and company considerations into account” - McKinsey. Incorporating several factors into the sensitivity score is necessary for several reasons.

For instance, price elasticity is based on different models for each product category, because customer behavior including purchase frequency and reaction to price-changes, differs for each product. By aggregating individual input factors for price sensitivity and promotion affinity, individual scores for each product category can be developed. With price sensitivity identified for all products, items are then grouped into three buckets based on their scores: top sensitivity, midlevel sensitivity, and low sensitivity.

TOP SENSITIVITY

Items falling into this category, according to McKinsey, are everyday products or key value items, such as common grocery items, whose prices most customers know, making it easy for them to compare shops.

As a result, customers are especially price sensitive when it comes to these products, and their prices must be competitive. These products typically account for 10 to 20 percent of a retailer’s sales. Investing in keeping their prices low, pays off in significantly better customer price perception, which leads to more frequent visits and larger baskets.

MIDLEVEL SENSITIVITY

The midlevel sensitivity or Foreground items have attributes that are more important to customers than price and hence do not require as great a degree of competitiveness in pricing as key value items. However, their prices should be competitive enough to avoid any negative impact on customers’ price perception.

Prices for these items can be set within a range that falls between, for example, the highest and lowest competitor prices, or the minimum margin and recommended retail price. LOW SENSITIVITY Items in the low sensitivity bucket are either products for which price is not an attribute that customers focus on much at all, or products for which a price comparison isn’t possible. Correspondingly, the products in this bucket offer the strongest opportunity for retailers to finance their investment in low prices for the key value items. 

BUILD A CLEARER PICTURE OF WHERE TO TARGET PROMOTIONS

After determining the factors that will help improve the accuracy of a price-sensitivity score, retail leaders need to rethink how they score promotions to better understand their impact on a particular product’s sales or profits. Promotion-affinity scores, according to McKinsey, primarily measures the impact of earlier promotions in terms of transaction- and customer-based success factors and basket composition.

The most important are increases achieved in revenue and margin. Depending on the specific situation, retailers can adjust the relative importance of five other factors: customers’ willingness to buy the product without a promotion, the increase in the number of transactions due to discounts, volume purchased of the product promoted, basket product variance, and any changes in buying behavior, such as more frequent store visits or larger baskets.

Finding the right path through this complexity requires two things: an overview of each relevant key performance indicator (KPI) that needs to be understood, and a way to express the cumulative results of all relevant KPIs. This cumulative KPI or “total customer effect” (TCE) shows how much additional revenue or margin a promotion accounts for by looking at what additional sales (or gross profit) it generates and whether it actually brought more customers into the store or increased the value of their baskets. 

OPTIMALLY LINK PRICES AND PROMOTIONS

To make better pricing and promotions decisions, companies need to then combine both scores in a price-promotion matrix so that an optimal balance can be identified for each product being sold. The retailer or marketing manager will then place the products into one of four quadrants of the matrix: High price sensitivity and high promotion affinity- Retailers using this approach respond to consumer sensitivity regarding prices for these products with a “low-low” approach— that is, both setting the lowest prices possible and maximizing discounts.

Also, they focus promotions on products in this category that specifically help to increase frequency of purchase or basket size. High price sensitivity and low promotion affinity- For these necessity-type products, leading retailers use a strategy of keeping regular prices low, at a level below the recommended retail price but above what a promotional price would be.

Low price sensitivity and high promotion affinity-These occasional purchases are given a “high-low” strategy, with prices that are close to the recommended retail or highest competitor prices but with discounts that lower promotional prices as much as possible. Leading retailers also vary promotion type, mix, and frequency, and they focus on product categories with high promotion affinity.

Low price sensitivity and low promotion Affinity- Leading retailers generate additional value with these products by increasing the margin earned on them. They price these items close to their highest competitors’ prices, and they reduce or stop promotions on them.

PRACTICAL APPLICATIONS

McKinsey first tested the approach in five product categories in a single country for periods ranging from four to six weeks. After this pilot phase was concluded successfully, the bulk of the results were carried over to other categories and countries and optimized further. Motivated by this success, the retailer has since launched a pricing-and-promotions transformation across other products and countries.

As a result, the company expects its sales revenue to increase by 3 to 5 percent and profits to grow by two to four percentage points over the three years following implementation of the approach. Also, its brand position has already improved and is far less dependent on discount promotions. This means that retail leaders need to build a clearer picture of where to target promotions.

Finding the right path requires an overview of each relevant KPI that needs to be understood, and a way to express the cumulative results of all relevant KPIs. The cumulative KPI shows the success of a specific promotion and whether it actually brought more customers into the store or increased the value of their baskets.

Effectively and profitably linking pricing and promotions together in this analytical method can increase revenue and profits by three to five percentage points overall. In addition, those companies that efficiently implement this approach often achieve improved customer satisfaction and loyalty as well

(Image: African Union Chairperson Moussa Faki Mahamat )

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African Union Commission Chairman Moussa Faki Mahamat is “observing quarantine” after a staff member in his office tested positive for COVID-19, an AU source told AFP....

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