Category Management: A Key Guide for CPG Companies

As a decision maker in the Consumer Packaged Goods (CPG) industry, you’re no doubt aware of the importance of staying ahead of the curve. 

With consumers increasingly demanding more personalized and convenient products, and competition from both established brands and up-and-coming disruptors, it can be challenging to keep up. This is where Category Management comes in.

In this blog post, we’ll explore what Category Management is, its benefits, key elements, steps to implementing a successful strategy, and challenges CPG companies may face in doing so.

What is Category Management?

At its core, Category Management is a strategic approach to managing product categories. It involves analyzing and understanding customer needs, assessing the competition and market trends, and developing and executing a plan that maximizes the value of a particular category to the business.

The goal is to increase sales, profit margins, and market share by offering the right products to the right customers at the right time, all while minimizing costs and improving operational efficiency.

Why is Category Management Important in the CPG Industry?

Category Management is particularly important, where margins can be tight and competition is fierce. By adopting a Category Management approach, CPG companies can:

Gain a better understanding of their customers and what they want, which allows them to tailor their product offerings and marketing strategies accordingly.

Increase the effectiveness of their promotions and pricing strategies, leading to increased sales and revenue.

Optimize their product mix and inventory levels, reducing waste and lowering costs.

Identify new growth opportunities by analyzing market trends and identifying unmet customer needs.

Benefits of Category Management

Some of the key benefits of Category Management include:

Increased Sales and Profitability

By analyzing consumer needs and buying behavior, Category Management can help CPG companies create more effective product assortments, promotions, and pricing strategies. This, in turn, can lead to increased sales and profitability.

For example, consider a CPG company that sells laundry detergent.

By using Category Management techniques to analyze customer needs, the company may discover that customers in certain regions prefer products with natural ingredients. By offering a natural detergent option in those regions, the company can increase sales to that particular customer segment.

Improved Operational Efficiency

Category Management can help CPG companies optimize their product mix and inventory levels, reducing waste and improving operational efficiency.

By focusing on the most profitable products and minimizing slow-moving or unprofitable items, companies can reduce costs and improve their bottom line.

Better Understanding of Market Trends and Competition

By analyzing market trends and assessing the competition, Category Management can help CPG companies identify new growth opportunities and stay ahead of the curve. This can include identifying emerging product categories or analyzing consumer behavior to identify new target markets.


In the next section, we’ll take a closer look at the key elements of a successful Category Management strategy.

Understanding the customer and their needs

One of the key elements of Category Management is understanding the needs and preferences of your target customers. This includes identifying the products and services that your customers are looking for, as well as the features and benefits that they value most. 

By understanding your customers’ needs, you can create more targeted and effective Category Management strategies that address those needs and differentiate your products from your competitors’.

Assessing the competition and market trends 

Another important element of Category Management is assessing the competitive landscape and market trends.

This involves monitoring the performance of your competitors, understanding their strategies, and identifying the strengths and weaknesses of their products and services. You should also stay up-to-date on the latest market trends and changes in consumer behavior that could impact your Category Management strategies.

Developing and executing a Category Management plan

Once you have a solid understanding of your customers and competition, you can develop and execute a Category Management plan. 

This plan should outline your Category Management goals and objectives, the strategies you will use to achieve those goals, and the tactics you will use to implement those strategies. 

It should also include a detailed timeline and budget, as well as metrics for measuring the success of your Category Management efforts.

Steps/Guide to Implement a Category Management Strategy

Conducting a Category Assessment: 

Before you can develop a Category Management strategy, you need to conduct a thorough Category Assessment. This involves analyzing the performance of your products and services, identifying any gaps in your product portfolio, and determining the key drivers of customer behavior in your category.

Defining Category Roles and Strategies: 

Based on your Category Assessment, you can define the roles and strategies for each of your product categories.

This involves determining which products should be prioritized, how to position those products to maximize sales, and which promotional tactics to use to drive customer engagement.

Implementing Category Tactics: 

Once you have defined your Category Roles and Strategies, you can implement specific tactics to achieve your goals.

This may include launching new products, optimizing pricing and promotions, and investing in marketing and advertising campaigns.

Evaluating and Adjusting Category Performance: 

Finally, it is important to regularly evaluate the performance of your Category Management strategy and make adjustments as needed.

This may involve analyzing sales data, conducting customer surveys, and monitoring market trends to ensure that your strategy remains relevant and effective.

Challenges of Category Management

While Category Management can offer significant benefits to CPG companies, there are also a number of challenges that must be addressed. Some common obstacles that companies face when implementing Category Management strategies include:

Data management challenges: With the increasing volume and complexity of data available to CPG companies, it can be difficult to effectively manage and analyze that data to inform Category Management strategies.

Siloed organizational structures:

Category Management requires collaboration and coordination across multiple departments and functions within a company. However, siloed organizational structures can make it difficult to achieve that collaboration and coordination.

Lack of resources: 

Implementing effective Category Management strategies requires significant resources, including time, money, and personnel. Smaller CPG companies may struggle to allocate those resources effectively.

Resistance to change: 

Finally, some employees may be resistant to changes in Category Management strategies, particularly if they have been successful with existing strategies in the past.

To overcome these challenges, CPG companies should focus on building a strong data management infrastructure, fostering a culture of collaboration and innovation, and investing in the resources and training needed to implement effective Category Management strategies.

How Explorazor helps Fortune 500 Companies with Category Management.

Explorazor is a data exploration tool that helps CPG companies optimize their categories by providing real-time data-driven insights. Here’s how:

Combining all datasets: We combine all datasets, including Nielsen, Kantar, Primary Sales, Secondary Sales, Media, and more, into one harmonized dataset into a single source of truth, eliminating the need to run around data custodians or extract pivots from multiple excel files.

AI engine: An AI engine, trained on data of Fortune 500 CPG companies, sends alerts and suggests action items. This helps brand managers make informed decisions based on real-time data.

Natural language processing: Once brand managers look at the performance, they can ask Explorazor questions in simple language, without troubling the insights team. This makes data-driven insights accessible to everyone in the organization.

Drill down: Losing market share? Brand managers can drill down across dimensions to figure out if the problem is in distribution or trade promotion and what exactly is the problem. This helps them identify the root cause of issues and take corrective action.

In conclusion, Category Management is a data-driven process that involves managing product categories to increase sales and profits. 

By using data-driven insights, CPG companies can optimize their categories and gain a competitive advantage. 

Explorazor’s data exploration tool is designed to help brand managers achieve this goal by providing real-time data-driven insights. With Explorazor, CPG companies can optimize their categories, improve customer satisfaction, and increase sales and profits.

Request a No-Obligation Demo today!

The Power of Influencer Marketing in CPG Industry

In today’s digital age, social media has become a powerful tool for businesses to connect with their target audience.

With the rise of social media influencers, influencer marketing has become an essential part of marketing strategies in the CPG (Consumer Packaged Goods) industry.

In this blog post, we will explore the benefits of influencer marketing in the CPG industry, successful influencer marketing campaigns, key strategies for influencer marketing, as well as challenges and risks associated with this type of marketing.

What is influencer marketing?

Influencers have a large following on social media platforms and can help brands reach a wider audience.

By partnering with influencers who have a similar target audience, CPG companies can tap into their followers and gain new customers.

According to a survey by Influencer Marketing Hub, 63% of consumers trust influencer recommendations more than brand advertisements.

This shows that influencers have a strong influence on consumer purchasing decisions.

By partnering with the right influencers, CPG companies can improve their brand reputation and credibility among consumers.

In addition, influencer marketing has higher engagement rates compared to other marketing strategies. Influencers have built a loyal following of engaged fans who trust their recommendations.

This means that sponsored content from influencers is more likely to be seen and engaged with by their followers, resulting in higher engagement rates for the brand.

Successful Influencer Marketing Campaigns in the CPG Industry

There are many successful influencer marketing campaigns in the CPG industry that have helped brands reach a wider audience and increase sales.

One example is the partnership between beauty brand Glossier and beauty influencer Emily Weiss.

Weiss founded Glossier and used her social media presence to promote the brand. Today, Glossier has a loyal following and has become a household name in the beauty industry.

Another example is the partnership between food brand HelloFresh and food blogger Damn Delicious.

HelloFresh partnered with Damn Delicious to create sponsored content featuring their meal kits.

This helped HelloFresh reach a wider audience and increase sales, while also providing Damn Delicious with a new source of income.

Finally, wellness brand Nike partnered with fitness influencer Kayla Itsines to promote their workout gear.

Kayla created sponsored content featuring Nike products and shared it with her followers. This helped Nike reach a new audience and improve their brand reputation among fitness enthusiasts.

How to implement a successful influencer marketing strategy?

To implement a successful influencer marketing campaign in the CPG industry, it is important to follow best practices.

One key strategy is to set clear goals for the campaign. This could be to increase brand awareness, improve engagement rates, or drive sales.

By setting clear goals, brands can measure the success of the campaign and adjust their strategy accordingly.

Another important strategy is to identify the right influencers for the campaign. 

Brands should partner with influencers who have a similar target audience and share similar values. It is also important to look for influencers who have a high engagement rate and a loyal following.

Creating engaging content is crucial for a successful influencer marketing campaign. Brands should collaborate with influencers to produce content that resonates with their followers and showcases the brand in a positive light. Additionally, many websites are now using text-to-speech generated videos to reach a wider audience by adopting AI technology.  

This could be through sponsored posts, videos, or social media takeovers.

Finally, measuring the success of the campaign is essential to ensure its effectiveness.

Brands should track metrics such as engagement rates, website traffic, and sales to determine the ROI of the campaign.

This information can be used to improve future campaigns and adjust the strategy accordingly.

Things which we need to keep in mind during Influencer Marketing

While influencer marketing has many benefits, there are also some challenges and risks associated with this type of marketing.

One challenge is the cost of partnering with influencers. Popular influencers often charge high fees for sponsored content, which can be a significant expense for brands.

Another challenge is ensuring that sponsored content is disclosed properly.

In the US, the FTC (Federal Trade Commission) requires influencers to disclose their partnerships with brands in their content.

Failure to disclose partnerships can result in fines and damage to the brand’s reputation.

There is also the risk of negative publicity if an influencer’s behavior or actions come under scrutiny. Brands need to ensure that the influencers they partner with have a clean reputation and align with the brand’s values and mission.

Finally, measuring the success of influencer marketing campaigns can be a challenge. While engagement rates and website traffic can be tracked, it can be difficult to determine the actual impact on sales and ROI.

This is where Explorazor comes in.

As a data exploration tool, Explorazor helps brand managers harmonize their different datasets and ask important questions to uncover insights that can drive growth and improve their influencer marketing campaigns.

With Explorazor, brand managers can easily deep dive into their data and identify root causes of issues, making it easier to optimize campaigns and improve ROI.

To see how Explorazor can help you unlock valuable insights from your data, request a demo today.

5 Ways Artificial Intelligence (AI) like ChatGPT is Revolutionizing CPG Industry

Artificial intelligence (AI) in the CPG industry has turned out to be a game-changing technology for businesses and enterprises.

With its ability to analyze large amounts of data, identify patterns and make predictions, AI is revolutionizing the way CPG companies operate and serve their customers.

The impact of AI can be seen across the entire CPG value chain, from production to marketing, supply chain management, and customer service.

This blog post will examine the various ways in which AI is transforming the CPG industry, including its benefits, challenges, and the future outlook.

By the end of this article, you will have a better understanding of the role of AI in the CPG industry and how it can help your business stay ahead of the curve.

Predictive Analytics and AI in CPG Industry

The use of artificial intelligence (AI) in predictive analytics is transforming the Consumer Packaged Goods (CPG) industry by providing insights that help companies make data-driven decisions. Predictive analytics is a process that uses data, machine learning, and statistical algorithms to make predictions about future outcomes based on historical data.

The benefits of predictive analytics include increased efficiency, cost savings, and improved decision-making. By using AI to analyze vast amounts of data from multiple sources, CPG companies can identify patterns and trends that would be difficult or impossible to detect manually.

Benefits of Using AI in Predictive Analytics in the CPG Industry

One of the primary benefits of using AI in predictive analytics is the ability to improve accuracy. With traditional methods, predicting outcomes based on historical data can be challenging due to the complexity of the data and the need to analyze multiple variables.

However, with AI, it is possible to analyze vast amounts of data quickly and accurately, allowing companies to make predictions with greater confidence.

Successful Implementations of AI in Predictive Analytics in the CPG Industry

One of the most successful implementations of predictive analytics using AI in the CPG industry is the use of AI-powered algorithms to predict demand for certain products during peak seasons or promotional periods.

By analyzing historical sales data and external factors such as weather patterns, these algorithms can accurately forecast demand and optimize inventory levels to ensure that products are available when customers want them.

For example, a CPG company might use AI to predict the demand for a particular product during a specific promotional period.

Based on the forecasted demand, the company can adjust production schedules and inventory levels to ensure that they have sufficient stock to meet customer demand. This can help to reduce waste and improve efficiency, as well as increase customer satisfaction by ensuring that products are always available when customers want them.

Another benefit of using AI in predictive analytics is the ability to identify patterns and trends that would be difficult or impossible to detect manually. For example, a CPG company could use AI to analyze social media data and identify emerging trends in consumer preferences.

By analyzing data from multiple sources, including social media, online reviews, and customer feedback, companies can gain a more comprehensive understanding of consumer behavior and preferences. This information can then be used to develop new products and marketing campaigns that better align with customer needs.

Personalization and Targeted Marketing with AI in CPG Industry

Personalization and targeted marketing are becoming increasingly important in the Consumer Packaged Goods (CPG) industry. With so many products available on the market, consumers are looking for brands that cater to their specific needs and preferences. This is where personalization comes in.

Why is Personalization important in CPG marketing

By personalizing their offerings, brands can create a unique customer experience that is tailored to each individual’s preferences. This can lead to increased customer loyalty, higher engagement, and ultimately, increased sales.

Benefits of Using AI in Personalization and Targeted Marketing

One of the ways that brands are achieving personalization and targeted marketing is through the use of artificial intelligence (AI). AI can help brands analyze vast amounts of customer data to identify patterns and trends that can inform targeted marketing campaigns.

For example, AI-powered algorithms can analyze customer purchase histories to identify which products they are most likely to buy in the future. Brands can then use this information to create targeted marketing campaigns that highlight these products and offer personalized promotions and discounts.

How are CPG companies adopting Personalization using AI in Marketing?

There are many successful examples of AI-powered personalization and targeted marketing in the CPG industry.

One such example is Coca-Cola’s “Freestyle” vending machines. These machines use AI-powered algorithms to offer customers personalized drink options based on their previous purchases. The machines use a touchscreen interface that allows customers to select from hundreds of different drink combinations, and they even offer suggestions based on the customer’s past choices.

Another example of AI-powered personalization is Amazon’s recommendation engine. By analyzing customer purchase histories and browsing behavior, Amazon is able to suggest products that are highly relevant to each individual customer. This not only improves the customer experience, but it also leads to increased sales for Amazon.

By using AI-powered algorithms to analyze customer data and identify patterns and trends, brands can create personalized customer experiences that lead to increased customer loyalty and sales.

AI-powered Supply Chain Management

Supply chain management is a critical function in the CPG industry. Ensuring that products are delivered to customers on time and in the right quantities is essential to maintaining customer satisfaction and maximizing profitability.

However, managing a complex supply chain can be challenging, particularly when dealing with large volumes of data and multiple stakeholders.

How AI helps improve Supply Chain Management for CPG Companies

By using AI-powered algorithms to analyze data from across the supply chain, brands can identify areas where efficiencies can be gained and costs can be reduced.

For example, AI can be used to optimize inventory levels, reducing the risk of stockouts and excess inventory. It can also be used to optimize transportation routes, reducing the time and cost of shipping products to customers.

Successful Implementations of AI in Supply Chain Management

One successful implementation of AI-powered supply chain optimization is PepsiCo’s “Smart Scan” program. This program uses AI to analyze data from across the supply chain, including sales data, inventory levels, and production schedules.

By analyzing this data, PepsiCo is able to identify areas where efficiencies can be gained, such as optimizing production schedules and reducing transportation costs. As a result, PepsiCo has been able to reduce its operational costs by millions of dollars each year.

Another example of AI-powered supply chain optimization is Nestle’s “WMS Vision” program. This program uses AI to optimize warehouse operations, including inventory management and order fulfillment. 

By analyzing data from across the warehouse, including product location and movement, Nestle is able to optimize its warehouse operations and reduce the time and cost of fulfilling orders.

By using AI-powered algorithms to analyze data from across the supply chain, brands can identify areas where efficiencies can be gained and costs can be reduced.

Quality Control and Assurance using AI

Quality control and assurance are essential aspects of the CPG industry. Consumers expect products that are safe, reliable, and consistent, and brands that fail to meet these expectations risk damaging their reputation and losing customers.

How can AI play a role in Quality Control and Assurance

This is where AI can be particularly helpful. By using AI-powered algorithms to analyze data from across the production process, brands can identify potential quality issues before they become major problems.

For example, AI can be used to monitor the production process in real-time, identifying any anomalies or deviations from the norm that could indicate a quality issue. AI can also be used to analyze customer feedback, identifying common issues or complaints that could indicate a quality problem.

Corporate Usage of AI in Quality Control and Assurance

One successful implementation of AI-powered quality control and assurance is Johnson & Johnson’s “CaringCrowd” platform. This platform uses AI to analyze customer feedback from across the company’s various product lines.

By analyzing this feedback, Johnson & Johnson is able to identify potential quality issues and take corrective action before they become major problems.

Another example of AI-powered quality control and assurance is Coca-Cola’s “QualityWise” program. This program uses AI to analyze data from across the production process, including ingredients, production methods, and packaging.

By analyzing this data, Coca-Cola is able to identify potential quality issues and take corrective action before the products are shipped to customers.

By using AI-powered algorithms to analyze data from across the production process and customer feedback, brands can identify potential quality issues and take corrective action before they become major problems.

AI-powered Customer Service and Support

Customer service and support are crucial aspects of the CPG industry. Consumers expect prompt and helpful support when they have questions or concerns about products, and brands that fail to meet these expectations risk losing customers and damaging their reputation.

AI to analyze customer inquiries and support requests

By using AI-powered algorithms to analyze customer inquiries and support requests, brands can provide more efficient and personalized support to their customers.

For example, AI can be used to provide automated responses to common inquiries, reducing the workload on customer support teams and allowing them to focus on more complex issues.

AI can also be used to analyze customer sentiment and feedback, identifying areas where products and support services can be improved.

Examples of AI in CPG industries for customer service and support.

One successful implementation of AI-powered customer service and support is Unilever’s “U-Studio” program. This program uses AI to provide personalized support to customers across the company’s various product lines.

By analyzing customer inquiries and support requests, U-Studio is able to provide more efficient and personalized support to customers, reducing the workload on customer support teams and improving overall customer satisfaction.

Another example of AI-powered customer service and support is Procter & Gamble’s “P&G Everyday” program. This program uses AI to provide personalized product recommendations and support to customers based on their individual preferences and needs. By analyzing customer data and behavior, P&G Everyday is able to provide more personalized and effective support to customers, improving overall customer satisfaction and loyalty.

How successful has the Adoption of AI been in the CPG industry?

To sum it up, the CPG industry is going through a significant transformation, and AI is playing a critical role in this evolution. With AI-powered solutions, CPG companies can optimize their supply chain, improve quality control and assurance, and deliver personalized marketing and customer support.

However, to achieve these advancements, businesses need a robust data exploration tool like Explorazor.

By providing quick and easy access to data insights, Explorazor empowers businesses to make informed decisions that can drive growth and customer satisfaction.

As the CPG industry continues to evolve, Explorazor will remain an essential tool for businesses that want to leverage the power of AI and stay ahead of the competition.

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The Ultimate Guide to Email Marketing for CPG Companies

As the world becomes increasingly digital, the consumer packaged goods (CPG) industry is faced with a critical question: how can companies adapt to the changing e-commerce landscape?

In the fiercely competitive world of consumer packaged goods (CPG), companies are constantly seeking new ways to boost sales and drive growth. With the advent of digital marketing, email marketing has emerged as a powerful tool for CPG companies to connect with their customers and drive sales.

We all know how important it is for businesses to stay ahead of the curve in marketing while remaining competitive.

In this blog post, we will explore the power of email marketing in the CPG industry, its benefits, and how it can help you increase your sales.

By the end of this post, you will have a clear understanding of why email marketing should be an integral part of your marketing strategy, and how you can use it effectively to connect with your target audience, drive sales, and achieve your business goals.

So, let’s dive in and discover the world of email marketing for CPG companies.

Understanding Your Audience

Email marketing has become an integral part of any successful marketing campaign. With an estimated 4.03 billion email users worldwide, email marketing has the potential to reach a vast audience.

Identifying the target audience for your email campaigns

However, to maximize the effectiveness of your email campaigns, it is important to understand your target audience. By creating buyer personas, you can gain insights into your audience’s pain points, interests, and preferences, allowing you to tailor your emails to their specific needs.

As a corporate employee of a CPG company, you understand the importance of identifying and understanding your target audience.

After all, your products are created with your customers in mind. It is essential to know who your target audience is and what they want. Creating buyer personas is a powerful way to achieve this.

Creating buyer personas to understand your audience’s pain points, interests, and preferences

Buyer personas are detailed profiles of your ideal customers. They are based on market research, customer data, and insights from your sales and customer service teams. Buyer personas include information such as demographic data, job titles, goals, challenges, pain points, preferred communication channels, and more.

By creating buyer personas, you can gain a deeper understanding of your audience’s needs and motivations, allowing you to create targeted and relevant email campaigns that resonate with your audience.

To create a buyer persona, start by gathering data from various sources, including market research, customer feedback, and your internal teams.

Look for patterns and commonalities in the data to identify key insights about your audience.

For example, you may find that your target audience is primarily made up of millennials who value sustainability and eco-friendliness.

Once you have gathered your data, it’s time to start building your buyer persona. Start by giving your persona a name and a job title.

This will help you to personalize your persona and make it more relatable. Next, include demographic information such as age, gender, income, and education level.

Then, delve deeper into your persona’s goals, challenges, and pain points. What are they trying to achieve? What obstacles are they facing? What are their biggest frustrations? This information will help you to understand what motivates your audience and how you can help them overcome their challenges.

Finally, consider your persona’s preferred communication channels and content preferences. Do they prefer email, social media, or direct mail? What types of content do they find most valuable?

This information will help you to create email campaigns that your audience will actually want to receive and engage with.

How to Build an effective Email List

In today’s digital age, email marketing remains one of the most effective ways for CPG companies to reach and engage with their target audience. Not only is it cost-effective, but it also provides a direct line of communication between your brand and your customers.

Importance of building an email list

However, to reap the benefits of email marketing, you need to have a quality email list. We will now discuss the importance of building an email list, best practices for building a quality email list, and ways to encourage sign-ups.

You understand that building an email list is essential to the success of your email marketing campaigns. Your email list is a valuable asset that allows you to communicate with your customers, build relationships, and drive sales.

A high-quality email list is made up of subscribers who have opted-in to receive your emails, are interested in your products or services, and are engaged with your brand.

But how do you build a quality email list? It’s not just about collecting as many email addresses as possible.

Instead, it’s about building a list of subscribers who are genuinely interested in your brand and are likely to engage with your emails. To achieve this, you need to follow best practices for building a quality email list.

Best ways to build a quality email list

First and foremost, you should always obtain permission from your subscribers before adding them to your email list. This means using opt-in forms and clearly communicating what they will be receiving from you.

Additionally, you should never purchase email lists or add email addresses without explicit consent. This not only violates anti-spam laws but also leads to low engagement rates and high unsubscribe rates.

Another best practice for building a quality email list is to segment your list based on your subscribers’ interests and behavior.

By doing so, you can create targeted email campaigns that are more likely to resonate with your audience. For example, you may want to segment your list based on purchase history, location, or engagement level.

Ways to encourage sign-ups

Encouraging sign-ups is also an essential part of building a quality email list. One way to do this is to offer something of value in exchange for their email address.

This could be a discount code, a free e-book, or access to exclusive content. You can also include opt-in forms on your website, social media profiles, and in-store signage.

Social media is another effective way to encourage sign-ups. By promoting your email list on your social media profiles, you can reach a wider audience and drive sign-ups. You can also use paid social media advertising to reach even more people.

By following best practices for building a quality email list, such as obtaining permission, segmenting your list, and encouraging sign-ups, you can create targeted and relevant email campaigns that resonate with your audience.

So, take the time to build a high-quality email list for your CPG company. It’s an investment that will pay off in the long run.

How to Craft an Effective Email

Now that you have built a quality email list, it’s time to craft effective emails that will engage your subscribers and drive results for your CPG company. The components of an effective email include a strong subject line, engaging and relevant content, a clear call-to-action, and personalization.

In this section, we will discuss tips for creating attention-grabbing subject lines, writing engaging and relevant content, and personalization techniques to make your emails more appealing to your audience.

As a brand manager, director, CXO, or VP of a CPG company, you know that your subscribers’ inboxes are inundated with countless emails every day.

So, how to make your email stand out and get opened?

The first step is to craft an attention-grabbing subject line. A strong subject line should be concise, descriptive, and compelling. It should entice your subscribers to open your email and find out more.

One way to create attention-grabbing subject lines is to use personalization.

Tips for creating attention-grabbing subject lines

This involves incorporating your subscriber’s name, location, or previous purchases into the subject line. Personalization can also extend to the content of your email, making it more relevant to your subscriber’s interests and behavior.

Once you have captured your subscribers’ attention with an attention-grabbing subject line, it’s time to focus on the content of your email. Your email content should be engaging, informative, and relevant to your subscribers. It should provide value to your subscribers and inspire them to take action, whether it’s making a purchase or visiting your website.

Writing engaging and relevant content

One way to create engaging and relevant content is to segment your email list based on your subscribers’ interests and behavior. By doing so, you can create targeted email campaigns that speak directly to your audience’s needs and preferences. For example, if you have subscribers who have purchased your products in the past, you can send them emails about new products or special promotions.

Another way to create engaging content is to use visual elements such as images or videos.

Visual content can help break up long blocks of text and make your email more visually appealing. It can also help convey your message more effectively

How personalization plays an important role in content creation for email marketing

Finally, personalization is key to making your emails more appealing to your audience. Personalization can take many forms, from using your subscriber’s name in the subject line to providing personalized product recommendations based on their previous purchases.

Personalization can help your subscribers feel valued and connected to your brand, which can lead to increased engagement and loyalty.

By understanding the components of an effective email, such as attention-grabbing subject lines, engaging and relevant content, clear call-to-actions, and personalization, you can create email campaigns that resonate with your audience and drive results for your CPG company.

So, take the time to craft effective emails that provide value to your subscribers and inspire them to take action. It’s an investment that will pay off in the long run.

Steps to Measure your Email Campaign Performance

We have now understood how the usage of both captivating subject lines and pers email marketing can be a powerful tool for reaching your audience and driving results.

However, to get the most out of your email campaigns, it’s important to track their performance and make data-driven decisions.

Key metrics to track in email marketing

We will now discuss key metrics to track in email marketing, tools for tracking email campaign performance, and strategies for improving email campaign performance.

One of the most important aspects of email marketing is tracking key metrics to evaluate the effectiveness of your campaigns.

These metrics include open rates, click-through rates, conversion rates, unsubscribe rates, and bounce rates.

Open rates measure the percentage of subscribers who opened your email, while click-through rates measure the percentage of subscribers who clicked on a link in your email.

Conversion rates measure the percentage of subscribers who completed a desired action, such as making a purchase or filling out a form.

Unsubscribe rates measure the percentage of subscribers who opted out of receiving future emails, while bounce rates measure the percentage of emails that were undeliverable.

Best Tools for tracking email marketing campaign performance

To track these metrics, you can use email marketing tools such as Mailchimp, Constant Contact, or Campaign Monitor.

These tools provide analytics dashboards that allow you to track your email campaign performance in real-time.

They also allow you to segment your email list, A/B test your campaigns, and automate your email marketing efforts.

Different ways through which we can improve the email campaign performance

To improve your email campaign performance, there are several strategies you can implement. 

One strategy is to optimize your email content for mobile devices. With more and more people accessing their emails on their mobile devices, it’s essential to ensure that your email content is easy to read and navigate on small screens.

Another strategy is to use A/B testing to test different variations of your email campaigns. A/B testing involves creating two versions of your email campaign and sending them to different segments of your email list. 

By comparing the performance of the two versions, you can determine which one is more effective and optimize your future campaigns accordingly.

As discussed above, Personalization is also key to improving email campaign performance.

By using your subscriber’s name, location, or previous purchases in your email campaigns, you can make them more relevant and engaging to your audience.

Personalization can also extend to the timing and frequency of your email campaigns, ensuring that your subscribers receive your messages at the right time and at the right frequency.

By tracking key metrics, using email marketing tools, and implementing strategies such as optimizing for mobile devices, A/B testing, and personalization, you can create email campaigns that resonate with your audience and drive results for your CPG company. 

So, take the time to track your email campaign performance and make data-driven decisions that will help you achieve your marketing goals.

Email Marketing Examples:

Email marketing has proven to be an effective tool for increasing sales and building brand loyalty. Many CPG companies have embraced email marketing as a key component of their overall marketing strategy, with impressive results

Examples of CPG companies that have successfully used email marketing to increase sales

For instance, Starbucks – In celebration of their 40th anniversary launched a personalized email campaign that used customer data to generate unique and personalized messages for each recipient.

The campaign resulted in a 10% increase in sales as per a report by Campaign Monitor.

Another example is Coca-Cola. They launched a holiday-themed email campaign that featured a virtual Santa Claus who delivered personalized messages to customers.

The campaign generated a 20% increase in open rates and a 73% increase in click-through rates.

Nestle launched an email campaign that featured personalized recipe suggestions based on customers’ dietary preferences and product purchases.

The campaign resulted in a 15% increase in sales.

Procter & Gamble launched an email campaign to promote their Tide PODS product line. The campaign used bold, eye-catching visuals and a simple, clear message to generate a 40% increase in click-through rates.

One of the key strategies that CPG companies use to maximize the effectiveness of their email campaigns is to create compelling content that resonates with their target audience.

For example, Johnson & Johnson’s BabyCenter creates email campaigns that provide valuable information to expectant and new parents.

Their emails contain tips on child-rearing, product recommendations, and other useful content that helps build trust and loyalty among their subscribers.

Similarly, Nestlé Purina’s email campaigns focus on pet care and provide valuable content that pet owners can use to improve the health and wellbeing of their pets. By providing valuable content that their subscribers find useful, these CPG companies are able to build strong relationships with their customers and increase the likelihood of repeat business.

How does Explorazor a Data Exploration Tool help Marketing Teams to get the Required insights?

In addition to compelling content and personalization, CPG companies also use data analytics to measure the effectiveness of their email campaigns and optimize their strategies accordingly.

For instance, PepsiCo uses A/B testing to determine which subject lines, images, and content are most effective in driving engagement and sales.

They also use analytics to track customer behavior and preferences, and then use this information to create more targeted and effective email campaigns.

Trusted by leading CPG & Pharma companies such as GSK, DANONE, Sanofi, Abbot, ALKEM and Olem, Explorazor helps combine all the datasets (Nielsen, Kantar, Primary Sales, Secondary Sales, Media, and more) into one harmonized dataset making it the single source of truth.

Once all the Datasets are added to Explorazor, rather than troubling the insights team, ask those questions to Explorazor in simple language and get the desired insights to your queries.

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Dynamic KPIs, Saving Filters as Groups, Updates to Root Cause Analysis and More – Explorazor Product Updates January 2023

We’re rapidly developing Explorazor to help Brand Managers conduct fast and efficient data exploration. Having already launched seamless root cause analysis, conditional formatting, dual and triple-axis charts in November’s release, we have made some other improvements this time around.

If you are yet to be acquainted with Explorazor, it is a CPG and pharma-specific data exploration tool laying the groundwork for skilled professionals to focus on solving real market problems instead of grappling with unstandardized data and slow laptops all the time. 

The Explorazor proposal for Brand Managers is to work on a harmonized dataset, accessible to all, facilitating instant data pivot extraction (via simple querying) and root cause analysis (via simple clicks) – saving time and effort while accelerating hypothesis testing rates. We do model and engineer your data for you as well.

Let’s look at January’s updates:

  1. Dynamic KPI creation

Users can get custom KPIs created as per their requirement, which are dynamically calculated for every query 

Let’s take an example of ‘Rate of Sales’ as a dynamically created KPI:

Simply insert ‘Rate of Sales’ as a keyword in your query as shown below:

The above image is an example of a dynamically created keyword. Users can get custom KPIs such as Rate of Sales, Market Share, etc. created as per their requirements.

It’s dynamic, so the query will be relevant all the time. As per your query, your numbers of the KPI will be calculated and updated in real-time. For example, you can get KPIs like ‘market share’ which can be calculated dynamically for brands, geography, or distribution, using the keyword, you can use the resulting table to create all kinds of visuals for presentation purposes, and/or perform root cause analysis on it.

  1. Filter Grouping

The rationale is simple – managers use a particular set of filters frequently. Typing in these set of filters repeatedly for every query is undesirable. 

Filter Grouping, as you’re smart enough to figure out by now, allows you to save a group of filters under a common header, and use it to apply the group of filters with ease in the future. Simply recall the header the next time you want to use that set of filters.

  1. Updates to Root Cause Analysis

Explore the root cause analysis/drill-down in detail in the linked blog. 

We have introduced more interactive elements to root cause analysis this time. To show important metrics for a data field, directly click on that field to display all its corresponding values in the left panel. 

This will be better understood with an example:

For any field you click, the numbers on the left panel change dynamically to reflect metrics for our area of interest.

An additional convenience here is the ability to sort the information on an ascending or descending basis. 

Some Other Updates

  1. Recently used keywords will now be prompted as suggestions as you type for quick access. A Google-like feature, and when it comes to a search interface, there’s no reason not to have it Google-like
  2. Min & Max query support is live
  3. There’s an option to edit live data connection options
  4. Updates to conditional formatting

That’s it for this time, and we’ll be back with more updates next month. Our goal remains the same: to help Brand Managers in CPG and Pharma focus only and only on data exploration, and create real impacts through it, with the ultimate objective of improving brand and company revenue. 


Explorazor is a product of vPhrase Analytics.

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Sales Per Million

Sales per million is the great equalizer. It is used to measure how fast your products are moving off the shelves in stores where they are in distribution, while controlling for distribution.

What this means is, suppose there are two markets where one is bigger than the other. Now how do you know if the smaller market sells at the same rate as the bigger market? Is the smaller market selling less because of market size, or is consumer demand weak in that area? Or, on the contrary, do products move faster in the smaller market? 

Sales per million takes into account the varying Total ACVs of different markets and stabilizes them in the denominator in its formula. Let’s look at the formula and then an example:

HOW TO CALCULATE SALES PER MILLION

Sales per Million is calculated as: 

Sales 

÷ 

%ACV distribution X (Market’s ACV ÷ 10,00,000)

‘Sales ÷ %ACV Distribution’ is the formula for ‘Sales per Point of Distribution (SPPD)’ which is used for checking velocity within a single market, or a single retailer. 

Also, ‘Sales’ here can be expressed in terms of units as well as in terms of rupees/dollars.

Market ACV has to be taken in the denominator to account for the size difference in ACV. Market ACVs are very large numbers, so we denote them in millions.

EXAMPLE – SALES PER MILLION

With the theory cleared, let’s understand the concept in practicality through an example:

Let’s suppose that the Mumbai market is 3x larger than Pune. The numbers below point to the same:

Observe that Pune’s Market ACV is significantly lesser than that of Mumbai. 

Now, let’s calculate Sales per Million using information from the above table:

For Product 1, Mumbai –

Sales = 65,000

%ACV Distribution = 80

Market ACV Size = 120 million

Sales per Million 

= 65000 ÷ [(80/100) x (120 million / 1 million) 

= 65000 ÷ [0.80 x (120)]

= 677

Similarly for all.

Pune’s sales velocity compared to Mumbai

  • For Product 1, is essentially the same 
  • For Product 2, has some discrepancy, but not too much
  • For Products 3 and 4, is very low

What’s the benefit here?

With the stakes equalized, we note that Product 3 and Product 4 are actually not doing well in Pune, and that cannot be attributed to Pune being a smaller market. The actual reason may lie in a weaker consumer demand, or lack of a suitable strategy for the city, or any other reason. 

It was calculation using Sales per Million that helped us identify that Pune needs more attention if products are to do well there. 

Note that one can use Sales per Million instead of SPPD (Sales per Point of Distribution) for single market/retailer calculation as well. While SPPD is easier to perform, managers who prefer uniformity in calculations do opt for Sales per million as against SPPD.
Refer to the blog on velocity for more detail on SPPD and Sales per million. Also invest 10 minutes each day to learn about ACV, %ACV, Average Items Carried, and the basics of TDP.

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The Painful Process of Making a Data-Backed Decision

Let’s explore the decision-making process that a business user, say a Sales Manager or a Brand Manager, goes through. The aim would be to identify the challenges they face during this process and explore a very relevant solution for that.

We’ll do this step-wise:

  1. The challenge is presented

Either the business user is actively analyzing a piece of information, looking for solutions, or a challenge presents itself, which s/he starts solving. 

For example, he observes that Total Sales in Region X has shown degrowth.

  1. Possible reasons are explored

Identifying the problem is the first step toward formulating a solution. Total Sales has shown degrowth, the first question that is raised is ‘Why’. For that, the Sales manager will look at whether his primary and secondary sales targets are being achieved or not.  

The Brand Manager, or the Data Manager, as they are called in certain roles, will go a little further to investigate other aspects that might help arrive at the reasons for the degrowth.

Some of the other areas that will be scrutinized are:

a. Market Data

First off, one sees how the market is performing. If my brand is down by 2%, but the entire category is down by 4%, then there’s no real cause for worry. For example, sales of ice cream are bound to go down during the monsoon season. 

Market data would also include the tracking, measurement and evaluation of marketing spends. It also includes surveying competition’s activities and correlating it to the change in sales of our own brand. 

b. Efforts Data

Are my people meeting the wholesalers as they were doing previously? In the case of the pharmaceutical industry, medical representatives meet doctors and provide them with promotional material or, say, medications, and follow a similar course of action with chemists as well. Another sub-component of the Efforts data would be to see if the team is following previously successful strategies or not.

c. Consumer Insights & Brand Health 

Datasets like Kantar provide valuable insights into customer behavior and psyche, how they can be expected to react to a particular promotional strategy, etc. It shares concrete data like Average Trip Size of a customer in a particular store.

Long-term focus areas such brand health, which is quite similar to brand perception, will also be kept a tab on.

3. Proactive or corrective action is undertaken 

Once the reason is pinpointed, managers can then begin setting up and rolling out implementation strategies.  

But before they can do that..

THE ISSUE OF WORKING WITH MULTIPLE DATASETS

Notice that we described the multiple datasets that managers work on in quite some detail. 

This is to bring your focus to the issues concerning working on multiple datasets 

  1. At the very least, time is wasted 
  2. The communication to acquire such datasets is another challenge in itself
  3. Cleansing and merging the datasets is also a painstaking process

By the time the manager gets around to testing assumptions and conducting analysis, much of time has been wasted and the effort that should have gone into analysis and exploration is allocated just readying the dataset for analysis and exploration.

SOLVING THE ISSUE OF WORKING WITH MULTIPLE DATASETS

Explorazor is a data exploration and analysis tool that has been designed to specifically solve this issue for Brand & Sales teams. On Explorazor, managers see a single, integrated view of all their datasets which they can query using simple keywords and obtain data pivots in seconds. It literally puts all of the data under a single roof and makes it available at the fingertips of managers. All of the data would be stored on cloud, accessible via browser.

Of course, Explorazor is not entirely utopian; not every user will obtain access to all the datasets a company possesses. Rather, customized projects will provide access to all relevant datasets that a user needs for his daily, weekly or monthly activities.

For more details, you can visit the Explorazor website, and if you are interested in knowing more in detail, visit Explorazor docs.

  1. Preparing visualizations and presenting the decision

To reiterate, the first three steps in the decision-making process were:

  1. Looking for a piece of information, or a challenge being presented 
  2. Exploration of possible reasons, which includes analyzing multiple datasets
  3. Undertaking proactive or corrective actions

The findings are then finally translated into a narrative to be presented to the management and/or the team. As a manager, you know what’s best for your company, and the all-important task of communicating forward-looking insights impactfully is best left to you. Explorazor seeks to remove the load of tasks that senior managers should not spend, or dare we say, waste their time in. 

To speed up hypothesis testing, provide independence in ad-hoc analysis, and enable managers to spend more and more of their time on tasks that add value to their brands and companies is what Explorazor is built for. 

To understand Explorazor better, contact us at support@vphrase.com and we’ll set up a short Explorazor demo for you. If you can’t find the time for that, we’ll be happy to share a one-pager with you for your reading. Enjoy!

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Interested in Becoming a Brand Manager? Know your IQVIA Data!

This blog aims to introduce budding Brand Managers to IQVIA and some of its data columns, to help them understand how IQVIA data helps Brand Managers in the pharmaceutical industry achieve their objectives. 

IQVIA, as its official website introduces, ‘is a leading global provider of advanced analytics, technology solutions and clinical research services to the life sciences industry dedicated to creating intelligent connections that deliver unique innovations and actionable insights’. We have also written similar articles on Kantar and Nielsen data, which you can find in our blog section.

Brand Managers in the pharmaceutical industry use IQVIA data to develop innovative strategies and drive brand sales and adoption. As we mentioned in a similar blog ‘Know Your Nielsen Data’ becoming a Brand Manager requires superior data handling skills and a pragmatic approach to data, where one can arrive at high-quality, real-life conclusions looking at hard numbers.

Just a word: Explorazor is supporting Brand Managers big-time with respect to analyzing their data. More on that later. And yes, Explorazor differs from Power BI.

IQVIA helps Brand Managers in the pharma industry:

  • Take decisions regarding brand expansion and advise ways how they can go about doing it, like analyzing growth potential, evaluating pipelines, understanding risk-opportunity ratio, the investment landscape, and more 
  • Adhere to market requirements, identify regulations, licenses, valuations and any potential market hurdle that may arise
  • Address customer needs better, by sharing information on the market behavior, competition’s performance, customer psychology and behavior, and even mapping a customer’s purchase journey
  • Achieve brand differentiation through timely delivery of evidence-based insights from across the globe. IQVIA’s competitive tracking processes cover and share information from more than 75 markets worldwide
  • Other ways that IQVIA data helps Brand Managers include risk evaluation and mitigation, networking with experts across clinical functions and obtaining intel & tracking of 45,000+ drug profiles and 10,000+ drugs

SOME DATASETS THAT BRAND MANAGERS DEAL WITH – IQVIA DATA

1. Sales Data

As with all other industries, the first thing that a Brand Manager in the pharmaceutical industry will look at is the performance of their Brand in the market, thereby referring to the sales data. There are 3 components to the IQVIA sales data:

  1. Sales Value
  2. Sales Volume
  3. Market Share

This sales data received from IQVIA is already classified geography-wise and product-wise as prescribed by the company.

2. Prescription Data

  1. Prescriptions Count

These are the total number of prescriptions via doctors recorded for a product

  1. Prescriptions per doctor (P/D)

 P/D refers to the avg. numbers of prescriptions for a brand.  It is captured specialty-wise, for example, General Physicians, Diabetologists, Oncologists, etc., and bifurcated on a Zonal level. The P/D ratio lets you know about the key specialties that contribute to the sales of your brand in the market.

3. Supply Chain Manager

From the manufacturer to the wholesaler to the final chemist or the outlet location, this dataset helps Brand Managers track end-to-end product flows. Logistics is a highly lucrative industry in and of itself if done right, and such datasets hold massive monetary implications for the company. It also helps the company be available where customers need them, where the market is thriving, or where there’s a gap to be exploited

4. Longitudinal Patient Data (LPD)

LPD data provides pharmaceutical companies with an understanding of disease treatment and how General Physicians are prescribing cures for them. This helps in new product development, as well as the evolution of current products in the portfolio. Another strong benefit of such a dataset is realized when formulating effective sales strategies for the on-field reps. 

There are many such datasets that Brand Managers work on. But here’s an important point:

DATA IS ONLY AS GOOD AS ITS LEVERAGE

We see from the above points that data literally can potentially impact everything – sales, customer service, supply chain infrastructure, competitive environment, etc.  What’s left is to

  1. Extract the best possible insights from it 
  2. In the minimum time possible 
  3. Another key element is to extract a higher number of high-quality insights from data within the same time frame.

Explorazor by vPhrase helps Brand Managers do all of the above. 

LEVERAGE DATA OPTIMALLY USING EXPLORAZOR 

Instead of multiple files from different data sources, the company’s own data sets, etc. what Brand Managers can do is simply choose to view a single, all-inclusive/integrated dataset on Explorazor, query it via simple keywords, and receive data pivots – at their fingertips.

Let’s just put some of the benefits in pointers, for easy reading:

  • The dataset is standardized, so manual labor is saved there 
  • One can start using Explorazor within the day, so there are no hiccups in adoption
  • Due to the integrated dataset, the extracted insights are high-quality
  • The lightweight design interface is custom-built to deliver speedy responses
  • All of this culminates in a Brand Manager wanting to dive deep and test out more hypotheses than before 
  • Speaking of deep dive, Explorazor also supports drill-down and drill-across into a particular data point. Simple click-and-dig, that’s all. See the image below

Some additional benefits: 

  • Tables can be converted to charts, graphs, and multiple other handsome-looking visuals (did we say handsome instead of beautiful? Oh well!)
  • Any data pivot can be transported to Excel by downloading it as a CSV
  • Any data pivot can be pinned to the ‘Dashboard’ for easy viewing 
  • In-project collaboration with team is possible via tagging/assigning of activities

And most important of all,

Custom made for Brand Managers, and that too primarily in FMCG and pharma. Of all the designations, we chose to dedicate our skills to help Brand Managers ease their daily activities, ironing out many data-related inconveniences they face. Explorazor continues to develop and provide a niche solution for Brand Managers.

Explrazor is a product of vPhrase Analytics. If you want to try out Explorazor for yourself, contact us at support@vphrase.com. It’s free, and it’s fun.

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Interested in Becoming a Brand Manager? Know Your Kantar Data!

As part of our 3-blog series to educate professionals wanting to become Brand Managers, we’ll be introducing you to some columns within the Kantar data that Brand Managers receive, and interact with, on a regular basis. 

The other two blogs in the series are:

For now, let’s look at some columns in the Kantar data and their brief explanations. We’ll be continuously updating this blog as well as the Nielsen blog over time, so be sure to bookmark and check them out once in a while!

 Let’s begin:

DATASETS THAT BRAND MANAGERS DEAL WITH – KANTAR DATA

  1. Households  

Households (HH) indicates the total number of households in the target market. This informs the Brand Manager of the total market potential that his/her brand can ideally target and reach

  1. Penetration 

Household Penetration is the number of households in which a brand is being used. Large brands such as Coca-Cola and Maggi rely heavily on increasing the HH penetration of their products. For this, they develop increasingly robust logistical networks, especially in high-potential countries like India where the majority of the population resides in rural areas. This data point also helps decide the allocation of billions of dollars of investment into advertising and promotions.

  1. Volume 

Vol, or Volume, is the total sales made. Volume could be sliced and analyzed, for example, in a particular time period or for a particular geography. This, of course, is one of the cornerstone data columns needed for progress – What are my sales figures? Which were my highest-selling areas? Which areas showed degrowth? are the fundamental questions that every Brand Manager starts with

EXPLORAZOR – FOR OBTAINING THE FUNDAMENTAL ANSWERS, FAST

Our data exploration tool, Explorazor, is built solely for Brand Managers to obtain answers from data at accelerated speeds. How? Brand Managers view a single, combined dataset on Explorazor, which they query using simple keywords, and obtain data pivots instantly. No switching between files at all.

You can view the 3 Types of Analysis Brand Managers can Perform Super-Easily on Explorazor.

BMs are also able to drill down and drill across to arrive at event root-cause, conduct ad-hoc analysis (independently, without support from Insights teams), and test out more hypotheses than ever before. There’s so much more to Explorazor as it plays its part in complementing Excel perfectly, so users do not have to leave Excel entirely, yet do away with some of Excel’s ‘rougher edges’, if we might call them that.

  1. Volume share

Volume share is the part of the market your brand has captured as against the total category share. This is a broad metric that lets a Brand Manager understand where s/he stands with respect to competition. Necessary remedial/preventive steps can then be taken to overtake the competition and increase the volume share, be it hiring more on-field forces or a from a completely different angle, say, increasing media spends to raise brand awareness in specific regions.

Explorazor again comes in handy when it allows Brand Managers to get all their queries answered at a single place, in addition to drill-down into a particular metric via simple clicks. 

  1. Avg Trip Size

The average trip size is understood as the average number of units bought by a consumer at one time/ in a single go. It is also understood as the average purchase weight per transaction. Since packet weights vary, a Brand Manager can potentially decide on a standardized purchase weight, which can be translated into how many packets of that particular weight were sold to a shopper during his/her visit.

With data on average trip size, a Brand Manager understands the distribution and stocking requirements of a particular store.

SIMPLIFYING DATA ANALYSIS – AND NOT JUST KANTAR

We hope these 5 points gave you a glimpse into the areas that Kantar data focuses on, and how Brand Managers can use these data points to elevate all aspects of their brand, like goodwill and sales. We want to further elaborate on how Explorazor can help Brand Managers achieve all of this in an extremely simplified manner.  

Explorazor holds all the datasets that a Brand Manager works on, and showcases them as a single integrated, standardized dataset on its interface. This includes all the separate Kantar columns we discussed, Nielsen data columns, IQVIA (in case of pharma), primary sales, secondary sales, market research, etc. 

Brand Managers pose queries, and data pivots are generated instantly. This speeds up the data analysis process, allowing Brand Managers to spend more time on strategizing and contemplation instead of conducting the manual labor of standardizing columns and querying multiple data sheets for a single insight. The data pivot on Explorazor can also be customized to produce visually appealing charts and graphs, and exported as CSV as needed.

We are on a quest to help Brand Managers ease their day-to-day data exploration process, relieve them of unwanted manual work and over-dependence on BI/Insights teams, enable them to conduct ad-hoc analysis and hypothesis testing at speed, and ultimately help them arrive at quality, target-smashing decisions.


Also understand how Explorazor differs from Power BI.

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How Kantar Data Helps Brand Managers in the CPG Industry

We’ll be exploring how Kantar data helps Brand Managers execute their responsibilities and take their brands to the next level. As the company’s official website introduces, Kantar ‘is the world’s leading data, insights and consulting company, helping clients understand people and inspire growth’. Kantar provides data on about 75 local and global markets, covering industries like CPG, Automotive & Mobility, Life Sciences, Retail, Media, Technology & Telecoms, and more.

Let us explore specifically how Kantar data helps Brand Managers, using the CPG industry as an example:

1. Understanding Markets, and Shoppers

Kantar data helps Brand Managers understand the complex purchase patterns of customers, both physical and virtual, in competing categories. It informs them of who is buying the brand and who isn’t. Kantar data also helps BMs understand the overall shopping trends and how competition operates.

Kantar’s specialty lies in:
– Their massive tracking system which captures the shopping decisions of 4,50,000 consumers all over the world
– Smart segmentation that unveils the best growth opportunities
– Competitor activity benchmarking, and
– Tracking behavioral and other types of trends over long periods

2. Growing the Brand and Extending to Newer Categories

Understanding what kind of buyers to target, the feasibility of entering new categories, based on the ability to satisfy what the consumer wants is another way Kantar data helps BMs. Consider also these points:

– Optimizing in-store ROIs via promotion, merchandising, etc.
– Influencing online shopper behavior by devising the right media and marketing mix components
– Hammering down the brand positioning and using existing insights as well as non-data analysis to model the brand structure, to drive sales
– Delving into category based on evidence that provides a futuristic perspective of shopper, category, and retail behavior

3. Driving Innovation

This is related to the classical 4Ps of marketing – how do you innovate your product? What promotional and pricing strategies do you use to sell it at scale? What kind of launch and distribution strategies are best?
Additionally, Brand Managers can use Kantar data to also delve into
– The impact that this innovation will have on the master brand and the brand architecture
– Ways to create the all-important ‘5th P’ – Packaging, for customer attraction
– Ways to optimize the brand portfolio and architecture, and
– Testing and development of concepts, products, and packs

4. Optimizing Investments

Data under this header relates to marketing and retail investment management for optimal returns. It studies
– The best way to conduct advertising spends
– Different digital contexts, examining them to see what works best
– Various touchpoint analyses, their impact and how to improve going ahead
– Various solutions used to drive sales and enhance field efficiencies

The Possibilities are Many

As we mentioned in the very first sentence, Brand Managers in the CPG industry can use Kantar data to take their brands to the next level. The data is there, and that is one part of two. The second falls upon Brand Managers to embark on an exploration journey where they truly analyze the plethora of information in front of them and carve out exceptional insights that serve as action points for the brand’s growth.

If Only Time was in Abundance

It seems heavy, but breaking it down to the simplest of factors tells us that Brand Managers simply do not have the time to conduct such in-depth exploration. This is due to the fact that such data comes in the form of loads of separate files, which are hard to simultaneously, and speedily, manage. Had Brand Managers the time for data exploration, the resulting insights and the subsequent impact of these insights on the brand would have been positively different.

We’ve Got a Present for You

At the risk of sounding cheesy, it’s the gift of time.

Explorazor gets the basics right – all of it. This data exploration tool combines all datasets, including Kantar, so BMs can query on an integrated dataset and receive instant data pivots.

There’s so much more on offer, as we’ve mentioned in other blogs such as ‘Interested in Becoming a Brand Manager? Know Your Nielsen Data!’.
Just read the conclusion, which starts with the header ‘SEPARATE FILE FOR EACH, OR JUST 1 INTEGRATED DATASET?’

Our pursuit is to help you use Kantar data to the fullest. See how, over a demo call.

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