Target the Top

July 12, 2017

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CPG manufacturers and retailers can evolve their promotional strategies to drive loyalty by digging deeper into data and creating truly personalized offers.

In today’s rapidly changing, digitally fueled marketplace, the competition is fierce – and customers’ expectations are even more demanding. Only by connecting with their best customers on a personal level will companies thrive.

The trick is not just collecting endless amounts of information – the big data that most companies are chasing – but knowing what to do with it, or having a third-party analytics partner that does. You can engage better with loyal customers by digging deeper into your customer data and creating personalized offers. When you successfully pursue personalization, you’re leveraging existing resources to increase sales – while driving loyalty.

Personalized offers

Let’s start with the fact that the results of broad-based trade promotions are frequently disappointing. According to the 2015 Nielsen Trade Promotion Landscape Analysis, 22% of trade promotions do not generate any sales lift, and 66% – a full two-thirds – fail to reach the break-even point.

Traditional trade promotions typically make a standard offer to the entire customer base using the retailer’s weekly flyer, a mass distribution channel that is typically deployed across all stores or, in a few cases, varied by ad zone (a group of stores in a similar geographic area).

Conversely, personalized offers target an individual through a unique identifier. To obtain those customer identifiers, marketers need a mechanism – such as a loyalty program, app or e-commerce site – that can capture the necessary data, as well as permissions. Personalized offers can then connect shopper strategies with product loyalty dynamics across in-store and digital channels.

Personalized offers also rely on an expanded set of media – including direct mail, email, text, web, social and mobile – to reach a specific person at a particular moment in time, and even on that person’s preferred device. Past purchase behavior can trigger an offer that can be extended dynamically by store, day of the week, time of day or other factors.

In reviewing the results of the 2016 Precima Grocery Promotional Research Study, it is clear there are certain types of shoppers who are most influenced by personalized promotions, including:

Specific generations

Millennials and Generation X members prefer personalized promotions and expect retailers to provide those customized options, perhaps because marketers are more capable of personalizing communications with those generations than they once were when boomers were younger. When thinking about promotions consumers receive now compared to three years ago, 66% of millennials and 63% of Generation X members receive more personalized offers and discounts, according to the 2016 Precima Promotional Study. Also, 66% of millennials and 59% in Generation X select their primary store based on the personalization of offers, versus 47% of boomers.

Tech-enabled

These individuals are more likely to take advantage of offers through mobile apps or SMS, and they prefer to pay via mobile. Who are these tech-enabled customers? Forty-five percent of millennials and 30% of those in Generation X select their primary store based on their ability to pay using a mobile device, versus 11% of boomers, according to the research. And 62% of millennials and 54% of Generation X members anticipate using their mobile phone more and more to view grocery offers, versus just 28% of boomers. Meanwhile, 50% of customers who spend $550 or more on groceries per month are more likely to use mobile phone to view offers versus just 37% of those who spend less than $74 on groceries per month.

Heavy spenders

These consumers are more likely than others to spend more than 40% of their weekly grocery budget at their primary store. With respect to key reasons for selecting a grocery store, 36% of those who spend 81% to 100% of their weekly budget at their primary store selected the store based on offers sent to their mobile device, versus 29% of customers who spend less than 40% of their weekly budget at their primary store.

Personalized offers are the next level in the ongoing efforts to execute successful one-to-one marketing strategies; that is, the ability to reach individual consumers with customized messages. In fact, personalized offers are almost becoming table stakes for some retailers, but there is still room for improvement and, ironically, it starts with improving traditional trade promotions. We encapsulate this roadmap-driven approach to personalization in six focal words: stop, fix, slant, relevance, incrementality and scalability.

The road to personalization is through traditional trade promotions

Traditional trade promotions have been a mainstay in the grocery industry for many years and have a significant impact on the business; this is not about to change overnight. The challenge is that traditional trade promotions absorb the majority of the promotional budget, which can starve personalization efforts of funding. So, what to do? 

Stop

This is where the first three of our six focal words come into play. Stop refers to quantifying past trade promotion performance so you can identify the trade promotions that should be stopped because they do not deliver meaningful results. The funds that are made available as a result of this process can be reinvested in personalized offers to help drive scalability. 

Fix

The next focal word is applied to trade promotions that are not top performers but have the potential to be top performers if they can be fixed. Fixing them involves ensuring that the discount depth is appropriate, or that they make appropriate use of flyer and/or display space, or that they are planned at the correct time of year or in the most appropriate stores.

Slant

Slant refers to the ability to select the trade promotions that appeal most to loyal customers and to tailoring discount depths to them. Doing so slants trade promotions toward the retailer’s best customers and disproportionately rewards those customers for their loyalty. For example, research from Precima shows the impact of different discounts on volume, revenue and profit on specific customer segments. In one instance, we found that overall revenue begins to decrease at the 40% discount level, but for the top-tier customers it begins decreasing after the 30% discount threshold. Tailoring the discount depth to 30% rewards loyal customers and saves trade funds that can be employed to run a second promotion that is slanted toward loyal customers (or, potentially redeployed to personalized offers).

Delivering on the promise of personalization

To truly deliver on the promise of personalization, we turn our attention to the second set of our six focal words: relevance, incrementality and scalability. Personalized offers must be relevant, but relevance is not sufficient in its own right. Trade promotions are great at driving incremental sales; personalized offers must ensure that they are also capable of delivering incrementality. Finally, personalized offers should also be able to meaningfully move the needle on overall sales. Trade promotions typically influence 10% to 40% of sales (depending on the retailer), and personalized offers must achieve this same level of engagement to succeed.

Relevance

Personalization efforts require a change in mindset – an evolution in thinking – in order to achieve relevance. Previously, marketers typically decided on a campaign or built an offer bank and then chose which customers to send offers to. However, to optimize personalized promotions, the first step must be to analyze the purchase behavior of customers to determine their needs and build a Total Store Offer Bank, and then design the campaigns and offers around the needs of each individual customer. Taking this approach can dramatically improve the relevance of offers to customers along multiple dimensions of each offer. The content and creative can be tailored for customers at different life stages and with different lifestyles. The featured products and discount offers can then be relevant for each individual customer.

This increase in relevance will lead to higher response rates, but that alone is not sufficient; high response rates with low incremental sales will not deliver the required returns, which is why it is important to also drive incrementality. 

Incrementality

If you simply give loyal customers offers for products they already purchase, you will drive high response rates and high customer satisfaction, but it will be challenging to achieve a positive ROI. You must also drive incremental sales as well as relevance and high response rates. Different shoppers have different levels of engagement; understanding the level of engagement by shopper is key to driving incrementality. The mix of offer types can be tailored based upon the level of engagement that each shopper has with the retailer: Loyal customers should receive the most thank-you offers for products that they already purchase; secondary customers should receive some thank-you offers plus some upsell and cross-sell offers; occasional shoppers should receive basket-builder or trip-driving offers.

Anyone who has shopped on Amazon.com has probably experienced the concepts of cross-selling and upselling; after adding an item to his or her cart, a shopper receives suggestions for other products to consider purchasing. There are two key analytical approaches that are typically used to drive cross-sell and upsell: like-customer analyses (“Customers like you also bought these items”) and product affinity analyses (“Customers who bought this product also bought these products”). These analytical approaches are used to drive upsell offers (suggesting the customer purchase the premium product versus the mid-tier product) and cross-sell offers (suggesting the customer purchase, for example, pita chips to accompany hummus).

Scalability

The final challenge for personalized offers is driving scalability into the overall process. A frequent refrain from senior retail executives is that personalized offers drive good response rates and campaign ROI but don’t impact sufficient customers or a sufficiently large chunk of sales to noticeably move the overall company sales number. Currently, this is a major disadvantage of personalized offers when compared to trade promotions.

Trade promotions benefit from significantly higher funding (mainly provided by CPG manufacturers) but also from a well-known process that has been established to allow CPG sales teams to work with their retailer category manager counterparts. No such scalable and well-understood process exists for personalized offers; the CPG consumer promotions team has very little direct contact with the retailer customer marketing team.

The funding imbalance can be addressed by a gradual reallocation of promotional funds from nonperforming trade promotions to better-performing personalized offers. Using a combination of a series of proof points from personalized offers and gains in the number of shoppers who want to receive these personalized offers, it’s possible to implement new, scalable processes that will achieve success.

Riding the wave requires the right balance

Most industry observers would agree that the waves of e-commerce and smartphone apps are not about to abate any time soon; in fact, most observers think they’re only going to increase in the coming years. These twin waves present great opportunities for retailers who are adept at adapting to trends, but they must be sure to maintain the right balance. This is true for grocers who are embarking on the journey to become truly omni-channel; pricing offers must be balanced across the store, e-commerce and smartphone apps. An integrated data and analytical platform that drives omni-channel personalization is the key, and it can take a retailer’s personalization efforts to new heights.

For example, you may find that 90% of your customers are happy with a shelf price of $1.99 for an item, but what happens to the other 10% of customers who are only willing to pay a lower price? The retailer could lower the price to the lowest desired price point and accept lower overall profits as a result. Alternately, the retailer could put the $1.99 price on the shelf and then provide personalized offers to the 10% of customers who want to pay a lower price. This approach achieves multiple objectives simultaneously: The retailer achieves their sales and profit targets while delivering a positive price perception and higher customer satisfaction. Doing so, however, requires an integrated approach. 

Tracking and improving

The good news is: The further you move down the personalization path, the greater the reward: The more personalized offers you deploy, the more data and insights you have. And having more data and insights means you can more deeply target and personalize future offers. It’s a productive loop that benefits both sides. 

  • Forty-two percent of North Americans are willing to provide personal information in exchange for tailored offers based on what they buy, according to the 2016 Precima Promotional Study.
  • Fifty-five percent of North American consumers are more willing to provide their personal information in exchange for special offers and events earmarked for certain best customers.
  • Sixty-one percent of consumers would give more personal information if companies sent relevant communications and product offers, according to the 2016 LoyaltyOne Consumer Sentiment Study.

In addition, personalized offers solidify and deepen customer relationships, enhancing loyalty that lasts the length of the customer life cycle. The 2016 Precima Promotional Study found that retailers still have some work to do when it comes to personalizing offers, as only 55% of shoppers are satisfied with the personalization of the offers at their primary store. While 55% is not a low percentage, it compares poorly with the satisfaction level expressed for other criteria – quality (95% satisfaction), regular prices (92%) and trade promotions (83%). CPG manufacturers and grocers must adopt personalization to thrive in a rapidly shifting, digitally oriented marketplace. Competition is fierce, and customer expectations will only increase. The companies that commit to connecting with their best customers – and meeting their needs on a personal level – will ultimately win.

Loyalty

Customer Analytics

Promotional Strategy

Grocery

Retail

Food Retail

Target the Top

Aug 27, 2018, 14:40 PM
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CPG manufacturers and retailers can evolve their promotional strategies to drive loyalty by digging deeper into data and creating truly personalized offers.

In today’s rapidly changing, digitally fueled marketplace, the competition is fierce – and customers’ expectations are even more demanding. Only by connecting with their best customers on a personal level will companies thrive.

The trick is not just collecting endless amounts of information – the big data that most companies are chasing – but knowing what to do with it, or having a third-party analytics partner that does. You can engage better with loyal customers by digging deeper into your customer data and creating personalized offers. When you successfully pursue personalization, you’re leveraging existing resources to increase sales – while driving loyalty.

Personalized offers

Let’s start with the fact that the results of broad-based trade promotions are frequently disappointing. According to the 2015 Nielsen Trade Promotion Landscape Analysis, 22% of trade promotions do not generate any sales lift, and 66% – a full two-thirds – fail to reach the break-even point.

Traditional trade promotions typically make a standard offer to the entire customer base using the retailer’s weekly flyer, a mass distribution channel that is typically deployed across all stores or, in a few cases, varied by ad zone (a group of stores in a similar geographic area).

Conversely, personalized offers target an individual through a unique identifier. To obtain those customer identifiers, marketers need a mechanism – such as a loyalty program, app or e-commerce site – that can capture the necessary data, as well as permissions. Personalized offers can then connect shopper strategies with product loyalty dynamics across in-store and digital channels.

Personalized offers also rely on an expanded set of media – including direct mail, email, text, web, social and mobile – to reach a specific person at a particular moment in time, and even on that person’s preferred device. Past purchase behavior can trigger an offer that can be extended dynamically by store, day of the week, time of day or other factors.

In reviewing the results of the 2016 Precima Grocery Promotional Research Study, it is clear there are certain types of shoppers who are most influenced by personalized promotions, including:

Specific generations

Millennials and Generation X members prefer personalized promotions and expect retailers to provide those customized options, perhaps because marketers are more capable of personalizing communications with those generations than they once were when boomers were younger. When thinking about promotions consumers receive now compared to three years ago, 66% of millennials and 63% of Generation X members receive more personalized offers and discounts, according to the 2016 Precima Promotional Study. Also, 66% of millennials and 59% in Generation X select their primary store based on the personalization of offers, versus 47% of boomers.

Tech-enabled

These individuals are more likely to take advantage of offers through mobile apps or SMS, and they prefer to pay via mobile. Who are these tech-enabled customers? Forty-five percent of millennials and 30% of those in Generation X select their primary store based on their ability to pay using a mobile device, versus 11% of boomers, according to the research. And 62% of millennials and 54% of Generation X members anticipate using their mobile phone more and more to view grocery offers, versus just 28% of boomers. Meanwhile, 50% of customers who spend $550 or more on groceries per month are more likely to use mobile phone to view offers versus just 37% of those who spend less than $74 on groceries per month.

Heavy spenders

These consumers are more likely than others to spend more than 40% of their weekly grocery budget at their primary store. With respect to key reasons for selecting a grocery store, 36% of those who spend 81% to 100% of their weekly budget at their primary store selected the store based on offers sent to their mobile device, versus 29% of customers who spend less than 40% of their weekly budget at their primary store.

Personalized offers are the next level in the ongoing efforts to execute successful one-to-one marketing strategies; that is, the ability to reach individual consumers with customized messages. In fact, personalized offers are almost becoming table stakes for some retailers, but there is still room for improvement and, ironically, it starts with improving traditional trade promotions. We encapsulate this roadmap-driven approach to personalization in six focal words: stop, fix, slant, relevance, incrementality and scalability.

The road to personalization is through traditional trade promotions

Traditional trade promotions have been a mainstay in the grocery industry for many years and have a significant impact on the business; this is not about to change overnight. The challenge is that traditional trade promotions absorb the majority of the promotional budget, which can starve personalization efforts of funding. So, what to do? 

Stop

This is where the first three of our six focal words come into play. Stop refers to quantifying past trade promotion performance so you can identify the trade promotions that should be stopped because they do not deliver meaningful results. The funds that are made available as a result of this process can be reinvested in personalized offers to help drive scalability. 

Fix

The next focal word is applied to trade promotions that are not top performers but have the potential to be top performers if they can be fixed. Fixing them involves ensuring that the discount depth is appropriate, or that they make appropriate use of flyer and/or display space, or that they are planned at the correct time of year or in the most appropriate stores.

Slant

Slant refers to the ability to select the trade promotions that appeal most to loyal customers and to tailoring discount depths to them. Doing so slants trade promotions toward the retailer’s best customers and disproportionately rewards those customers for their loyalty. For example, research from Precima shows the impact of different discounts on volume, revenue and profit on specific customer segments. In one instance, we found that overall revenue begins to decrease at the 40% discount level, but for the top-tier customers it begins decreasing after the 30% discount threshold. Tailoring the discount depth to 30% rewards loyal customers and saves trade funds that can be employed to run a second promotion that is slanted toward loyal customers (or, potentially redeployed to personalized offers).

Delivering on the promise of personalization

To truly deliver on the promise of personalization, we turn our attention to the second set of our six focal words: relevance, incrementality and scalability. Personalized offers must be relevant, but relevance is not sufficient in its own right. Trade promotions are great at driving incremental sales; personalized offers must ensure that they are also capable of delivering incrementality. Finally, personalized offers should also be able to meaningfully move the needle on overall sales. Trade promotions typically influence 10% to 40% of sales (depending on the retailer), and personalized offers must achieve this same level of engagement to succeed.

Relevance

Personalization efforts require a change in mindset – an evolution in thinking – in order to achieve relevance. Previously, marketers typically decided on a campaign or built an offer bank and then chose which customers to send offers to. However, to optimize personalized promotions, the first step must be to analyze the purchase behavior of customers to determine their needs and build a Total Store Offer Bank, and then design the campaigns and offers around the needs of each individual customer. Taking this approach can dramatically improve the relevance of offers to customers along multiple dimensions of each offer. The content and creative can be tailored for customers at different life stages and with different lifestyles. The featured products and discount offers can then be relevant for each individual customer.

This increase in relevance will lead to higher response rates, but that alone is not sufficient; high response rates with low incremental sales will not deliver the required returns, which is why it is important to also drive incrementality. 

Incrementality

If you simply give loyal customers offers for products they already purchase, you will drive high response rates and high customer satisfaction, but it will be challenging to achieve a positive ROI. You must also drive incremental sales as well as relevance and high response rates. Different shoppers have different levels of engagement; understanding the level of engagement by shopper is key to driving incrementality. The mix of offer types can be tailored based upon the level of engagement that each shopper has with the retailer: Loyal customers should receive the most thank-you offers for products that they already purchase; secondary customers should receive some thank-you offers plus some upsell and cross-sell offers; occasional shoppers should receive basket-builder or trip-driving offers.

Anyone who has shopped on Amazon.com has probably experienced the concepts of cross-selling and upselling; after adding an item to his or her cart, a shopper receives suggestions for other products to consider purchasing. There are two key analytical approaches that are typically used to drive cross-sell and upsell: like-customer analyses (“Customers like you also bought these items”) and product affinity analyses (“Customers who bought this product also bought these products”). These analytical approaches are used to drive upsell offers (suggesting the customer purchase the premium product versus the mid-tier product) and cross-sell offers (suggesting the customer purchase, for example, pita chips to accompany hummus).

Scalability

The final challenge for personalized offers is driving scalability into the overall process. A frequent refrain from senior retail executives is that personalized offers drive good response rates and campaign ROI but don’t impact sufficient customers or a sufficiently large chunk of sales to noticeably move the overall company sales number. Currently, this is a major disadvantage of personalized offers when compared to trade promotions.

Trade promotions benefit from significantly higher funding (mainly provided by CPG manufacturers) but also from a well-known process that has been established to allow CPG sales teams to work with their retailer category manager counterparts. No such scalable and well-understood process exists for personalized offers; the CPG consumer promotions team has very little direct contact with the retailer customer marketing team.

The funding imbalance can be addressed by a gradual reallocation of promotional funds from nonperforming trade promotions to better-performing personalized offers. Using a combination of a series of proof points from personalized offers and gains in the number of shoppers who want to receive these personalized offers, it’s possible to implement new, scalable processes that will achieve success.

Riding the wave requires the right balance

Most industry observers would agree that the waves of e-commerce and smartphone apps are not about to abate any time soon; in fact, most observers think they’re only going to increase in the coming years. These twin waves present great opportunities for retailers who are adept at adapting to trends, but they must be sure to maintain the right balance. This is true for grocers who are embarking on the journey to become truly omni-channel; pricing offers must be balanced across the store, e-commerce and smartphone apps. An integrated data and analytical platform that drives omni-channel personalization is the key, and it can take a retailer’s personalization efforts to new heights.

For example, you may find that 90% of your customers are happy with a shelf price of $1.99 for an item, but what happens to the other 10% of customers who are only willing to pay a lower price? The retailer could lower the price to the lowest desired price point and accept lower overall profits as a result. Alternately, the retailer could put the $1.99 price on the shelf and then provide personalized offers to the 10% of customers who want to pay a lower price. This approach achieves multiple objectives simultaneously: The retailer achieves their sales and profit targets while delivering a positive price perception and higher customer satisfaction. Doing so, however, requires an integrated approach. 

Tracking and improving

The good news is: The further you move down the personalization path, the greater the reward: The more personalized offers you deploy, the more data and insights you have. And having more data and insights means you can more deeply target and personalize future offers. It’s a productive loop that benefits both sides. 

  • Forty-two percent of North Americans are willing to provide personal information in exchange for tailored offers based on what they buy, according to the 2016 Precima Promotional Study.
  • Fifty-five percent of North American consumers are more willing to provide their personal information in exchange for special offers and events earmarked for certain best customers.
  • Sixty-one percent of consumers would give more personal information if companies sent relevant communications and product offers, according to the 2016 LoyaltyOne Consumer Sentiment Study.

In addition, personalized offers solidify and deepen customer relationships, enhancing loyalty that lasts the length of the customer life cycle. The 2016 Precima Promotional Study found that retailers still have some work to do when it comes to personalizing offers, as only 55% of shoppers are satisfied with the personalization of the offers at their primary store. While 55% is not a low percentage, it compares poorly with the satisfaction level expressed for other criteria – quality (95% satisfaction), regular prices (92%) and trade promotions (83%). CPG manufacturers and grocers must adopt personalization to thrive in a rapidly shifting, digitally oriented marketplace. Competition is fierce, and customer expectations will only increase. The companies that commit to connecting with their best customers – and meeting their needs on a personal level – will ultimately win.

Tags :
  • Customer Analytics
  • Food Retail
  • Grocery
  • Loyalty
  • Promotional Strategy
  • Retail
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