1) Introduction
We’ve heard it said again and again, “happy customers are loyal customers”.
After all, in world-famous marketing strategist Seth Godin’s words: “It’s easier to love a brand when the brand loves you back”. And it’s easy to see why.
People appreciate feeling valued and important. Especially when they’re paying money in exchange for services or goods.
And if there’s one way of ensuring customer satisfaction, that’s customer experience.
Customer experience is the entire journey and interactions a customer has with a brand.
Naturally, this will depend on customer satisfaction, i.e. contentment and fulfilment with that experience.
According to statistics quoted by Forbes, 87% of customers will make further purchases from a company if they had a great experience the first time round. Just 18% would do the same if they had a very poor experience.
Similarly, a study carried out by Salesforce revealed that 88% of customers say the experience a company provides is as important as its product or services — rising from 80% in 2020. The same 2022 study showed that 71% of consumers reported they switched brands at least once in the past year, with 48% of them saying they did so because of better customer service.
A great customer experience doesn’t just make happier customers. It makes happier businesses too. According to a Hubspot article, customer-centric companies are 60% more profitable than those that aren't. So it’s not just a matter of customer satisfaction and loyalty, it’s also a matter of profit, and overall business success.
Great customer experience, whether spread through traditional word of mouth or virtual means, significantly improves the odds of people recommending a company, product, or service.
According to research by CustomerGauge, a 10+ increase in the Net Promoter Score (NPS), the leading market research metric for measuring the probability of customer recommendations, results in a remarkable 3.2% upsale revenue increase.
Similarly, Bain & Company's research indicates that a company's NPS can account for approximately 20% to 60% of the variation in organic growth, empowering businesses to thrive and outpace their competitors.
The stakes are becoming increasingly high, especially in today's competitive business landscape. This means customer experience must be considered a top priority, and treated as such.
However, navigating customer experience isn’t as straightforward as one would hope.
Fortunately, there are numerous tools available that can significantly reduce guesswork and optimise resources and finances, for both brick-and-mortar businesses, but also for online businesses.
Among the most reliable solutions is location intelligence, a data-backed solution that can provide valuable insights into customer behaviour, preferences, and overall market trends.
Through this information, businesses can make better-informed decisions, tailor experiences, and allocate resources efficiently, ultimately enhancing customer satisfaction and driving business growth.
Plus, they can gain a fair competitive edge in meeting evolving customer expectations, making it a win-win for both parties: both your clients and your business, too.
In this guide, we’ll be providing you with five ways you can boost your customer experience with two types of data:
Sentiment: reveals customer emotions and opinions, providing valuable insights for businesses
Popularity: shows the most-frequented businesses, neighbourhoods and territories, supplying businesses with an overview of the volume, and demographic of people in the area.
By the end of this guide, you'll have a comprehensive understanding of these data types and how to effectively leverage them, enabling you to stay ahead of the curve and establish your industry leadership in delivering exceptional customer experiences.
2) Understanding Sentiment Data
Have you ever wondered what people truly think about your business or brand?
Sentiment data aims to provide businesses with that precious, yet often unattainable information.
And, you don’t even need to ask directly for it.
Sentiment data can be derived from various online sources, such as social media platforms, customer reviews, and online discussions. Through its analysis, businesses can get an in-depth insight into the real perception, opinion, and emotions of their current, or potential audience regarding that business’s products, service, and overall brand experience.
This wealth of information is gold for businesses. Usually, directly asking for feedback can be laborious, time- and resource-consuming.
Using such traditional methods alone may also lead to biassed feedback. Not all respondents feel comfortable sharing their opinions about their customer experience.
Some may only provide socially desirable responses. Similarly, certain feedback may not always be representative of the true sentiment because of the timing of the request, or because the survey is not representative of the entire customer base.
Through data-backed sentiment analysis, businesses can identify the true sentiment and opinion through a variety of online platforms, allowing them to gain a more accurate and nuanced understanding of their audience’s needs, expectations, and preferences.
Sentiment data analysis and customer experience
Undoubtedly, this sort of information can help shape an optimal customer experience. The more you understand how your customers feel, what they need, prefer, and eventually buy — both throughout their online and offline journeys — the more you can make decisions that reflect the way they make their choices.
Based on sentiment analysis, you can identify the strengths and weaknesses of each individual shop or online shop and act accordingly to improve the customer experience. You can, for example:
By making these changes, businesses can deliver highly- personalised, and exceptional experiences by understanding what they’re doing right (based on positive sentiment), and what they can improve (based on negative sentiment), and focus their efforts and budgets accordingly to enhance customer satisfaction, foster long- term loyalty, and boost their business health and success.
3) Understanding popularity data
Now, instead of getting to know what people think about your business, imagine discovering which neighbourhoods and territories have the highest popularity.
The great thing is, you won't need to be Sherlock Holmes or whip out a magnifying glass to investigate these areas.
Instead, you’ll need popularity data.
Popularity data refers to the measurement of the number of people visiting a particular location, such as a store, event, or website, over a specific period.
Similar to sentiment data, popularity can give an invaluable look into customer behaviour, trends, and overall demand.
Popularity is mainly based on footfall data, that is, the number of visits in a real-world location. Through these figures, businesses can determine peak hours, understand customer traffic patterns, and use this information to optimise their resources such as staffing, and budget allocation. By measuring these figures, businesses can make better-informed decisions about investment decisions such as where to open their store, or choosing their suppliers and distributors.
It’s also an important factor to assess the effectiveness of marketing campaigns, promotions, or events — serving as a powerful tool to understand preferences, while enhancing operational efficiency and to cater to the demands of their target audience.
Popularity data analysis and customer experience
Customer experience depends on popularity data analysis. By understanding the number of visitors to a physical location, businesses can gain valuable insights into customer behaviour and preferences; which in turn is critical for optimising store layouts, product and resource placement, and creating a more intuitive and pleasant customer journey.
Additionally, businesses can use popularity data to measure the impact of marketing campaigns and events on customer foot traffic and use this information to refine their strategies to attract and retain more customers.
4) Combining sentiment and popularity data for better customer experience
If sentiment and popularity data have such a big impact on customer experience on their own, think of the revolutionary power they hold when combined.
In this section, we’ll look at five ways sentiment and popularity data can shape your customer experience, and take it to the next level.
5) Elevate your customer experience with Data Appeal
Regardless of the industry you operate in, embracing sentiment and popularity data is the way forward to shaping your customer experience according to the modern customer’s needs.
As the world changes rapidly, so do the needs and preferences of people around the world. And gauging their emotions, opinions, and behaviours in real-time is making the difference between businesses that remain relevant, and those that can’t keep up with the rhythm at which industries are evolving.
Similarly, the urban landscape is under constant shift. Neighbourhoods change their composition, reputation, and overall identities in a matter of years, if not months. As a result, businesses must adapt to not only thrive in this realm of change, but also optimise their budgets and resources to customer flows to enhance shopping experiences.
Data Appeal’s sentiment and popularity data have already revolutionised hundreds of customer experiences businesses offer all around the world.
Our Sentiment Score provides you with a complete overview of your business’s online reputation by analysing all content posted by users on over 130 online sources, normalising scores and producing a synthetic index from 0 to 100.
Our Popularity Index, on the other hand, estimates attendance in any given area — territory of business — through digital content, with a time slot projection where available. When available, you can filter points of interest by peak time, discovering the time of day they are most frequented.
All our data is available either as a data pack and API, through our versatile options: D / AI Data Ready and D / AI API Connect, as an indexing solution, or in data visualisation format using common GIS systems, such as Esri, QGIS, Carto, and other similar platforms.
1. Introduction
2. Understanding sentiment data
3. Understanding popularity data
4. Combining sentiment and popularity data for better customer experience
5. Optimise your customer experience with Data Appeal
1) Introduction
We’ve heard it said again and again, “happy customers are loyal customers”.
After all, in world-famous marketing strategist Seth Godin’s words: “It’s easier to love a brand when the brand loves you back”. And it’s easy to see why.
People appreciate feeling valued and important. Especially when they’re paying money in exchange for services or goods.
And if there’s one way of ensuring customer satisfaction, that’s customer experience.
Customer experience is the entire journey and interactions a customer has with a brand.
Naturally, this will depend on customer satisfaction, i.e. contentment and fulfilment with that experience.
According to statistics quoted by Forbes, 87% of customers will make further purchases from a company if they had a great experience the first time round. Just 18% would do the same if they had a very poor experience.
Similarly, a study carried out by Salesforce revealed that 88% of customers say the experience a company provides is as important as its product or services — rising from 80% in 2020. The same 2022 study showed that 71% of consumers reported they switched brands at least once in the past year, with 48% of them saying they did so because of better customer service.
A great customer experience doesn’t just make happier customers. It makes happier businesses too. According to a Hubspot article, customer-centric companies are 60% more profitable than those that aren't. So it’s not just a matter of customer satisfaction and loyalty, it’s also a matter of profit, and overall business success.
Great customer experience, whether spread through traditional word of mouth or virtual means, significantly improves the odds of people recommending a company, product, or service.
According to research by CustomerGauge, a 10+ increase in the Net Promoter Score (NPS), the leading market research metric for measuring the probability of customer recommendations, results in a remarkable 3.2% upsale revenue increase.
Similarly, Bain & Company's research indicates that a company's NPS can account for approximately 20% to 60% of the variation in organic growth, empowering businesses to thrive and outpace their competitors.
The stakes are becoming increasingly high, especially in today's competitive business landscape. This means customer experience must be considered a top priority, and treated as such.
However, navigating customer experience isn’t as straightforward as one would hope.
Fortunately, there are numerous tools available that can significantly reduce guesswork and optimise resources and finances, for both brick-and-mortar businesses, but also for online businesses.
Among the most reliable solutions is location intelligence, a data-backed solution that can provide valuable insights into customer behaviour, preferences, and overall market trends.
Through this information, businesses can make better-informed decisions, tailor experiences, and allocate resources efficiently, ultimately enhancing customer satisfaction and driving business growth.
Plus, they can gain a fair competitive edge in meeting evolving customer expectations, making it a win-win for both parties: both your clients and your business, too.
In this guide, we’ll be providing you with five ways you can boost your customer experience with two types of data:
Sentiment: reveals customer emotions and opinions, providing valuable insights for businesses
Popularity: shows the most-frequented businesses, neighbourhoods and territories, supplying businesses with an overview of the volume, and demographic of people in the area.
By the end of this guide, you'll have a comprehensive understanding of these data types and how to effectively leverage them, enabling you to stay ahead of the curve and establish your industry leadership in delivering exceptional customer experiences.
2) Understanding Sentiment Data
Have you ever wondered what people truly think about your business or brand?
Sentiment data aims to provide businesses with that precious, yet often unattainable information.
And, you don’t even need to ask directly for it.
Sentiment data can be derived from various online sources, such as social media platforms, customer reviews, and online discussions. Through its analysis, businesses can get an in-depth insight into the real perception, opinion, and emotions of their current, or potential audience regarding that business’s products, service, and overall brand experience.
This wealth of information is gold for businesses. Usually, directly asking for feedback can be laborious, time- and resource-consuming.
Using such traditional methods alone may also lead to biassed feedback. Not all respondents feel comfortable sharing their opinions about their customer experience.
Some may only provide socially desirable responses. Similarly, certain feedback may not always be representative of the true sentiment because of the timing of the request, or because the survey is not representative of the entire customer base.
Through data-backed sentiment analysis, businesses can identify the true sentiment and opinion through a variety of online platforms, allowing them to gain a more accurate and nuanced understanding of their audience’s needs, expectations, and preferences.
Sentiment data analysis and customer experience
Undoubtedly, this sort of information can help shape an optimal customer experience. The more you understand how your customers feel, what they need, prefer, and eventually buy — both throughout their online and offline journeys — the more you can make decisions that reflect the way they make their choices.
Based on sentiment analysis, you can identify the strengths and weaknesses of each individual shop or online shop and act accordingly to improve the customer experience. You can, for example:
By making these changes, businesses can deliver highly- personalised, and exceptional experiences by understanding what they’re doing right (based on positive sentiment), and what they can improve (based on negative sentiment), and focus their efforts and budgets accordingly to enhance customer satisfaction, foster long- term loyalty, and boost their business health and success.
3) Understanding popularity data
Now, instead of getting to know what people think about your business, imagine discovering which neighbourhoods and territories have the highest popularity.
The great thing is, you won't need to be Sherlock Holmes or whip out a magnifying glass to investigate these areas.
Instead, you’ll need popularity data.
Popularity data refers to the measurement of the number of people visiting a particular location, such as a store, event, or website, over a specific period.
Similar to sentiment data, popularity can give an invaluable look into customer behaviour, trends, and overall demand.
Popularity is mainly based on footfall data, that is, the number of visits in a real-world location. Through these figures, businesses can determine peak hours, understand customer traffic patterns, and use this information to optimise their resources such as staffing, and budget allocation. By measuring these figures, businesses can make better-informed decisions about investment decisions such as where to open their store, or choosing their suppliers and distributors.
It’s also an important factor to assess the effectiveness of marketing campaigns, promotions, or events — serving as a powerful tool to understand preferences, while enhancing operational efficiency and to cater to the demands of their target audience.
Popularity data analysis and customer experience
Customer experience depends on popularity data analysis. By understanding the number of visitors to a physical location, businesses can gain valuable insights into customer behaviour and preferences; which in turn is critical for optimising store layouts, product and resource placement, and creating a more intuitive and pleasant customer journey.
Additionally, businesses can use popularity data to measure the impact of marketing campaigns and events on customer foot traffic and use this information to refine their strategies to attract and retain more customers.
4) Combining sentiment and popularity data for better customer experience
If sentiment and popularity data have such a big impact on customer experience on their own, think of the revolutionary power they hold when combined.
In this section, we’ll look at five ways sentiment and popularity data can shape your customer experience, and take it to the next level.
5) Elevate your customer experience with Data Appeal
Regardless of the industry you operate in, embracing sentiment and popularity data is the way forward to shaping your customer experience according to the modern customer’s needs.
As the world changes rapidly, so do the needs and preferences of people around the world. And gauging their emotions, opinions, and behaviours in real-time is making the difference between businesses that remain relevant, and those that can’t keep up with the rhythm at which industries are evolving.
Similarly, the urban landscape is under constant shift. Neighbourhoods change their composition, reputation, and overall identities in a matter of years, if not months. As a result, businesses must adapt to not only thrive in this realm of change, but also optimise their budgets and resources to customer flows to enhance shopping experiences.
Data Appeal’s sentiment and popularity data have already revolutionised hundreds of customer experiences businesses offer all around the world.
Our Sentiment Score provides you with a complete overview of your business’s online reputation by analysing all content posted by users on over 130 online sources, normalising scores and producing a synthetic index from 0 to 100.
Our Popularity Index, on the other hand, estimates attendance in any given area — territory of business — through digital content, with a time slot projection where available. When available, you can filter points of interest by peak time, discovering the time of day they are most frequented.
All our data is available either as a data pack and API, through our versatile options: D / AI Data Ready and D / AI API Connect, as an indexing solution, or in data visualisation format using common GIS systems, such as Esri, QGIS, Carto, and other similar platforms.
1. Introduction
2. Understanding sentiment data
3. Understanding popularity data
4. Combining sentiment and popularity data for better customer experience
5. Optimise your customer experience with Data Appeal
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