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Customer Engagement

9 Quantitative Research Methods With Real Client Examples

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Photo Credit: Patricia Gortari/Tallwave

Quantitative research is essential to developing a clear understanding of consumer engagement and how to increase satisfaction.

Primary Quantitative Research Methods

When it comes to quantitative research, many people often confuse this type of research with the methodology. The research type refers to style of research while the data collection method can be different.

Research types

These are the primary types of quantitative research used by businesses today.

  • Survey research: Ideally when conducting survey research businesses will use a statistically relevant sample to understand the sentiments and actions of a large group of people. This could be their current customers or consumers who fit into their ideal demographic.
  • Correlational research: Correlational research compares two variables to come to a conclusion about whether there is a relationship between the two. Keep in mind that correlation does not always imply causation, which is to say you need to account for external variables that could cause an apparent relationship.
  • Experimental research: This form of research takes a scientific approach, testing a hypothesis by manipulating certain variables to understand what changes this could cause. In these experiments, there is a control group and a manipulated group.

Also read: 6 Factors Influencing Customer Behaviors in 2021

Data collection methods

Launching the above research requires creating a plan to collect data. After all, quantitative research relies on data. Here are the common primary data collection methods for quantitative research.

 

  • Surveys: A common approach to collecting data is using a survey. This is ideal especially if the business can obtain a statistically relevant sample from their responses. Surveys are often conducted through web or email questionnaires.
  • Interviews: Yes, interviews can be used to obtain quantitative data. While this form of data collection is typically associated with qualitative research, interviewers can ask a standard set of questions to collate formal, quantitative data.
  • Documentation review: With an increasing amount of business occurring digitally, there is more documentation now than ever before to help inform quantitative conclusions. Businesses can assess website metrics such as return visits, time on page or even use a pixel to track customer movement across websites. They can also view how many times their app has been opened and actions users have taken on their platform to determine customer engagement.

Secondary research can be helpful when formulating a plan for obtaining primary quantitative data. It can help narrow areas of focus or illuminate key challenges.

Secondary Quantitative Research Methods

Secondary data is information that is already collected and not necessarily exclusive to the company but still relevant when understanding overall industry and marketplace trends. Here are a few examples of secondary data:

  • Government reports: Government research can indicate potential regulatory roadblocks, customer pain points and future opportunities. For example, a fitness company might use government data that shows an increase in use of outdoor running trials to develop a new product used to meet that specific use case.
  • Survey-based secondary data: Polls or surveys that have been conducted for a primary use could be reused for secondary purposes. This could include survey data obtained by other companies or governments.
  • Academic research: Research that has been previously conducted and published in peer-reviewed journals can help inform trends and consumer behavior, even if it doesn’t apply to a company’s specific customers.

Secondary research can be helpful when formulating a plan for obtaining primary quantitative data. It can help narrow areas of focus or illuminate key challenges. It can also help when it comes to interpreting primary data, especially when trying to understand the relationship between two variables of correlated data.

Also read: The What, Why, & How of Customer Behavior Analysis

Real Examples of Quantitative Research

We regularly use quantitative research to help our clients understand where they can best add value to increase customer engagement. Here are three examples of quantitative research in motion.

Example 1: Leading food distribution company

We helped a leading food distribution company identify changes in the needs and values of their restaurant clients as a result of COVID-19. This helped inform opportunities to become more valuable partners.

 

The research plan involved creating a survey that was emailed to clients. The questions were specific and numeric. For example, respondents were asked what percentage of their weekly spend was used with the food distribution company. They were also asked to assign a percentage to the way their food ordering had changed during COVID-19 and to rate their satisfaction with the food distribution company.

 

The results showed changes that had occurred for clients of the food distribution company as a result of the unique stressors of the pandemic. We were able to determine changes in weekly food supply and customer count as well as menu adaptations and purchase behavior.

 

Example 2: Leading credit card company

Our work with a leading credit card company required us to understand what current travel card members valued about the rewards program and their preferred communication method for booking travel in order to create an omnichannel servicing strategy and ideal customer journey.

 

Through an online survey of younger cardholders, the target demographic for this project, we asked questions such as length of card membership, total spend and the number of annual leisure trips in addition to more specific questions that showed how members get inspiration for trip planning and where they research.

 

The results highlighted ways to overcome resistance to pricing by proving more value. It also illuminated ways to make the benefits of membership more tangible to card holders and how to influence travelers in the early stages of planning their journey.

Example 3: Internal research report

We’re in the business of drinking our own champagne, so to speak, which is why we conducted our own quantitative research aimed at understanding the consumer trends that were spurred by the pandemic and how these will transform behaviors in the future.

 

There’s no question that new customer experiences emerged from the pandemic. Think of offerings such as “buy online, pickup in store (BOPIS),” or blended restaurant meals that are cooked at home. We wanted to understand how consumers truly felt about these new experiences and which they were likely to continue using even after restrictions were lifted. We also wanted to know more about the changing expectations for branded communication and how all of these pieces of the puzzle fit together to create consumer engagement. Our method of data collection was a survey.

 

Our research led us to develop insights we could use to inform our customers in their decision making. For example, we found convenience is paramount for consumers who are seeking out hybrid experiences such as BOPIS to take the best of both worlds. We also found many of these changes are permanent as consumers embraced new experiences that made their lives easier.

We regularly use quantitative research to help our clients understand where they can best add value to increase customer engagement.

The Bottom Line

Quantitative research is essential to developing a clear understanding of consumer engagement and how to increase satisfaction. Though online surveys are one of the most common methods for obtaining data, research isn’t limited to this strategy. It’s important to use whatever strategies are within your scope to constantly evaluate new trends and consumer behaviors that could significantly impact your offerings. The results can show you how to re-engage customers and drive loyalty.

 

Interested in partnering with us to learn more about your customers needs, wants, and behaviors to inform future experience design? Contact us today!

Categories
Customer Engagement Uncategorized

9 Metrics That Help Measure Customer Engagement

Measuring customer engagement
Photo Credit: Patricia Gortari/Tallwave

Gaining new customers is only half the battle when it comes to sustaining a healthy business — keeping customers engaged and loyal to your company long-term is just as important. Sometimes, that’s easier said than done, especially considering the changing nature of customer preferences.

 

Most companies are challenged with constantly iterating their customer engagement strategies. Oftentimes larger enterprise companies bear more of that brunt in order to maintain market share as more agile upstarts join the scene.

 

Also read: Data Driven Insights Into the Evolving Customer Experience 

 

Case and point: A large entertainment and communications firm – despite having experience that predates the internet – came to us with plummeting retention rates. Identifying the cause of their customer churn was essential to strategizing and implementing an improved experience for the future. By conducting research to understand the end-to-end customer journey, we were able to uncover and map out internal and external stakeholder perspectives at each stage. Using that information, we identified which stages in the journey had the greatest impact on customer loyalty. Then we were able to create a prioritized list of suggested improvements to enhance the customer experience and drive a greater bond between the business and their audience.

 

It’s this kind of work that can make the world of difference when it comes to increasing customer engagement.

 

Reducing friction and inspiring trust are the cornerstones of customer engagement today. A recent Salesforce study found that 95% of consumers said trust makes them more likely to remain loyal while 80% said the customer experience is just as important as the product or service.

 

Reviewing the journeys your customers take helps to identify ways to increase convenience and drive engagement, which is essential for success. Here are some top methods to measure customer engagement.

Reducing friction and inspiring trust are the cornerstones of customer engagement today.

Top Customer Engagement Metrics

There are a variety of metrics you can use to create a full picture of your customer experience and increase customer engagement. Here are some of the most frequently used methods::

1. Net Promoter Score (NPS)

NPS is the leading metric for measuring customer satisfaction and loyalty. This is accomplished by asking customers one, simple question to rate the likelihood that they would recommend a company, product or service to a friend or colleague. The rating is on a scale of 0 -10, with zero being “not at all likely” and 10 being “extremely likely.”

 

How to calculate: Respondents are divided into three groups based on their score.

 

  • Promoters: (rated 9-10) are loyal customers who will also refer others to your company.
  • Passives: (rated 7-8) are satisfied, but not enthusiastic.
  • Detractors: (rated 0-6) are unhappy customers and could potentially damage your brand by spreading negative reviews.

To calculate your NPS score, subtract the percent of Detractors from the percent of Promoters. Here’s what the formula looks like: % Promoters – % Detractors = NPS. Your NPS can range anywhere from -100 to 100 depending on your ratio of promoters to detractors.

% Promoters - % Detractors = NPS

How it infers customer engagement: Your NPS score is a good measure of your customers’ overall perception of your brand. Customers who fit the Detractor category are unhappy, these are the customers most likely to speak poorly about your brand to others or leave negative reviews. Customers who fit the profile of Passives are not excited about your business and are unlikely to be loyal if a competitor comes along with a sweeter offer. Customers who are considered Promoters are not only loyal, but will act as ambassadors for your company. It’s best to compare your NPS to others in your industry and also to your past scores to monitor any changes in your customers’ perceptions.

 

Also read: The What, Why, & How Of Customer Behavior Analysis

 

Best for: This classic customer engagement tool is best for gaining a high-level understanding of customer experience and how loyal your customers are.

2. Customer Satisfaction (CSAT)

CSAT is short for Customer Satisfaction Score. It is a popular metric to gauge customer satisfaction levels for a specific product/service or action you took rather than an ongoing customer relationship.. A CSAT score is expressed as a percentage (100% to 0%). Using the results from a customer surveys that ask respondents to “Rate their overall satisfaction with the goods/services they received. Respondents use the following 1-5 scale:

 

1 = Very Dissatisfied (or Very Bad)

2 = Somewhat dissatisfied (Poor)

3 = Neither satisfied nor dissatisfied (Neutral)

4 = Somewhat satisfied (Good)

5 = Very Satisfied (Excellent)

 

How to calculate: To understand your CSAT, you’ll want to divide the number of satisfied customers (represented by those who responded with a 4 or 5 ) by the total number of customers.

 

Use this formula to calculate: Number of satisfied customers (4 and 5) / Number of survey responses) x 100 = % of satisfied customers

Number of satisfied customers (4 and 5) / Number of survey responses) x 100 = % of satisfied customers

How it infers customer engagement: Your CSAT score is helpful to measure customer satisfaction after an experience or touchpoint with your business. It’s not typically used to represent customer engagement over time, since it’s a snapshot of how each individual customer was feeling during the exact circumstances of the survey.

 

Best for: CSATs are typically easier to collect than other data points because you’re not asking a lot of your customers. CSATs are also easily understood across many channels of your organization. This makes them ideal for creating company-wide benchmarks that you can update consistently.

3. Customer Lifetime Value

Your customer lifetime value indicates how much your company can expect to earn across an entire relationship with a customer from start to finish. Segmenting your customers by lifetime value can help your company get strategic about the most important groups to engage for long term revenue growth.

 

How to calculate: Before you can calculate the customer lifetime value, you need to know the average customer value. You do this by determining the average purchase value and then multiplying that by the average number of purchases. That first formula looks like this: Average Purchase X Average Number of Purchase = Customer Value.

Average Purchase X Average Number of Purchase = Customer Value

Then, put that number into the following formula: Customer Lifetime Value = Customer Value X Average Customer Lifespan.

Customer Value X Average Customer Lifespan = Lifetime Value

How it infers customer engagement: It goes without saying that the happier your customers are with your product or service, the more likely they are to continue purchasing renewals or upgrades. Focusing on improving your customer lifetime value typically means you’ll surround customers with support and incentives, which can also lead to higher customer engagement scores. Best for: Compare your customer lifetime value to the cost of acquiring new customers so you can understand if your value realization is strong enough to offset the marketing or sales costs associated with generating demand.

4. User Activity

User activity measures how many unique customers are interacting with your product or service in a specific time frame — typically daily or monthly. This is an ideal customer engagement metric for SaaS companies or apps.

 

How to calculate: Calculating daily user activity hinges on accurately defining what you’ll consider a user and an activity. To get a strong sense of how users are interacting on your platform, you might want to count actions such as pulling reports or collaborating with team members instead of merely sign ons or app opens.

 

How it infers customer engagement: By measuring activities that would only happen if the user was engaged — like creating reports, for example — you can begin to understand how often your users are incorporating your features into their lives. If you notice some features are under-utilized, this could be a warning sign that your customers aren’t fully engaging with the potential of your offerings.

 

Best for: This metric is best for understanding what features of your product are most engaging for customers, so you can continue to iterate on these and improve your value realization opportunities.

 

Also read: How to Holistically Map the Customer Experience

5. Visit Frequency

Measuring the visit frequency shows you how often the same customer returns to your site or store location. This helps you to understand how familiar your customers are with your brand and the extent to which they are actively seeking your company.

 

How to calculate: Using Google Analytics, you can pull a count-of-session report to understand visit frequency to your website. Measuring visit frequency for brick-and-mortar locations has historically been more difficult, but new technology, such as Ripple Metrics, can actually measure return frequency in addition to other actions your customers take in store.

 

How it infers customer engagement: If you have many of the same customers returning over time, this shows a higher level of engagement. However, if you have customers visiting your site or location once and not returning, this shows you have more work to do in order to foster customer loyalty.

 

Best for: Visit frequency can be seasonal. For example, if you work at an oil change garage, you might only expect customers to return once every six months. That’s why measuring visit frequency is a good metric for companies that understand what the patterns of a happy customer look like. Gain clarity on the big picture of your customer journey so your visit frequency inferences will be valuable.

 

6. Screentime

Measuring how long a customer spends on your site can tell you how valuable your content is and the extent to which you are helping to make the lives of your customers easier. If your customers spend a long time reading an article or watching a video, congratulations, that means you gave them something to stick around for.

 

How to calculate: Using your website analysis tools, you can pull a report to specify the total time on site or get specific to understand how long customers are spending on each page.

 

How it infers customer engagement: If you notice customers are routinely spending a few seconds on each page, that could be a sign that your website content is not engaging. Typically the first action users take when they realize a webpage doesn’t have the information they need is to close it and move on to the next one. This metric can help you determine what content is hitting home with your customers and what needs more work.

 

Best for: This metric is essential if you rely on content marketing to drive sales or improve the customer experience.

Understanding your customer engagement isn’t always a matter of gathering the most information, but of understanding which metrics to focus on.

7. Pages per Session

Pages per session shows you the average number of pages a visitor to your website reads before they leave your website. Similar to screentime, this metric can show you the extent to which visitors are enjoying your website and gaining value from it.

 

How to calculate: You can determine the pages per session by dividing the total page views by the total amount of sessions for any given time period. If you use Google Analytics, this number should automatically be pulled for you through the program’s standard reporting in the acquisition overview section. To get more detailed, remember to segment by source. You might find that visitors coming from one channel are more heavily engaged, which could influence how you spend advertising dollars.

 

How it infers customer engagement: If you have a high number of pages per session it’s likely visitors to your site are finding a lot of useful information and that you are providing a quality user experience. If you find this metric drops over time, it could signal that you need to revisit your content or maintain your website.

 

Best for: Use this metric to understand how well your website is performing when it comes to serving your customers.

 

8. Churn Rate

Your churn rate measures the number of customers who are concluding their relationship with your business over a set period of time. For example, if you are a service with subscribers your monthly churn rate would show the percentage of users who have cancelled their subscription each month.

 

How to calculate: Calculating your churn rate is simple, just divide the number of customers who have stopped doing business with you by the total number of customers. For example, if you have 20,000 subscribers and 1,000 cancelled last month, you would have a churn rate of 5% for the month.

 

How it infers customer engagement: If you have a high churn rate you can infer that somewhere along the line your customers are becoming disappointed. You’ll need to do some work to understand where in the journey they are seeing less value so you can improve these pain points and extend the customer lifespan.

 

Best for: This is a good metric for softwares or subscription services that rely on monthly recurring revenue.

9. Social Media Engagement

Your social media engagement can show you how interested your customers are in hearing from you and sharing about the work you do. A high social media engagement rate doesn’t always equate to increased sales, but it can definitely help guide your team to know if you’re on the right track in developing rapport, loyalty and strong word-of-mouth.

 

How to calculate: To get a high-level view of your social media engagement, measure your average engagement rate by adding the total number of engagements on a given post (this includes likes, comments and shares) by your total number of followers.

 

How it infers customer engagement: If your social media engagement numbers are low, this could be a sign that you need to do more work providing daily value to your current customers to turn them into brand evangelists. Not all companies rely on social media though, so if your social engagement numbers are low but you have another channel that does well, such as a newsletter, you might want to weigh both sets of metrics against each other before taking action.

 

Best for: Social media engagement can help companies understand how well they are doing when it comes to creating brand awareness and enthusiasm.

Bottom Line

Understanding your customer engagement isn’t always a matter of gathering the most information, but of understanding which metrics to focus on. Every brand should choose a handful of metrics that matter most to their business operations. Depending on your goals, there are only a few metrics that should be tracked regularly to gauge engagement, loyalty, value realization and growth. For the client we mentioned at the start of this article, we were trying to solve for high customer churn. We decided to narrow available data down so we were only focusing on mapping customer satisfaction. We felt this metric could most accurately predict churn. By understanding where in the journey customers were least satisfied, we were able to identify where drop off occurred.

Curious how the evolving customer experience is changing customer sentiment? Check out our recent research report, or contact us today.

Categories
Value Realization

Defining & Maximizing Value Realization For Customers

Lens into customer sentiment
Photo Credit: Patricia Gortari/Tallwave

But when and where does value realization occur? Well, that depends. Value realization can vary by product or service, and – depending on the priorities and needs of the consumer – can be very subjective.

 

Take, for example, a new pair of Nike running shoes. Value realization doesn’t typically occur at the purchase point within the customer journey. Instead, the customer realizes the true value of the shoes when he or she looks in the mirror and thinks, “Wow, these look great!” Or takes them for that very first run and notices an improvement in comfort and support. Or wears them about town and receives a compliment from a stranger or friend.

 

For CPG products like Coca-Cola, value realization may occur when customers take that first sip to quench thirst or receive a caffeine-boost of energy.

Value realization is the idea that there’s some point within your holistic customer journey when the value of the product or service is fully realized. It’s that realization that can illuminate the path for future and ongoing engagement, retention, and opportunities for upsells. Each business has to find and understand where value occurs for their customers and try to measure the moment by proxy. This unveils opportunities for change and innovation to then bring that moment of value realization further up the funnel.

Value realization isn’t always a metric. Oftentimes, it’s more of a concept. It’s an idea that there’s some point within your holistic customer journey when the value of the product or service is fully realized.

Pinpointing Moments of Value Realization

As with most things, you must start the crusade for quick value realization by going back to the basics and evaluating your business’s offering and delivery method inside and out.

 

More often than not, businesses and brands create products and services with their own goals and ideas top of mind. While this may result in experiences that please internal stakeholders, it isn’t always optimized for the customer or end user that you’re trying to engage and reach. Instead, you need to create a customer experience and evaluate value delivery from the perspective of the intended consumer. And in some cases, you may have to manufacture and intentionally test moments to pinpoint specific opportunities to drive or accelerate value realization.

 

For example, we work with a SaaS company who developed an AI-powered search and discovery platform. Right now, they – like many software companies – provide a compelling free trial that strives to demonstrate value in quick, small ways in order to convert trial users to regular users. While they may be able to leverage data to quantify users’ activities, and track and understand customers, an upgrade or purchase doesn’t actually reflect value realization. In fact, a conversion doesn’t guarantee a user has even had a customer experience that includes that coveted moment of truth, yet.

Instead, to truly gauge opportunities for value realization, they may consider building an interactive tool that comes pre-loaded with several data templates. In doing so, a product developer and potential customer can quickly approximate how the tool might work with their environment and enable them to realize the value right away. Airtable and Asana, for example, do this very well.

 

A proactive approach like this can help eliminate ambiguity associated with value realization and give businesses back the reins, by allowing them to manufacture (and measure and iterate!) a singular moment of truth.

 

Also read: How to Holistically Map Your Customer Experience

Understanding the True Value of a Product or Service For Customers

This is easier said than done. It seems simple – most business leaders and innovators think they know the bottom-line value being offered to consumers – but when in the thick of things, striving to grasp the big-picture and bring it to life, the actual value that’s felt by customers can get lost in the larger dream.

 

Also read: Data Driven Insights Into the Evolving Customer Experience

Instagram is a great case study of this. The now-immensely popular and profitable app was first brought to life in 2009 under the name Burbn by Kentucky whiskey lover and hobbyist coder Kevin Systrom. In Its first life, it functioned as a location-based app (inspired by Foursquare) and allowed users to check-in at places, make plans for future check-ins, earn points for visits, and post pictures of get togethers. The thing was – it had so many features that it was too complicated, and therefore, not all that successful. But it had potential. Systrom analyzed and evaluated how users were engaging with the app over time and then brought in a second programmer – Mike Krieger – to help. By leaning into analytics and mapping user behavior, Systrom and Krieger discovered that the check-in features were a complete flop. No one was using them. They were, however, enthusiastically using the photo-sharing feature. So, with a new sense of clarity, Systrom and Kriefer stripped the app down, studied new potential competitors, and released Burbn 2.0 – an easy photo-sharing app named Instagram. The rest is history.

 

Considering that example – where did value realization occur? Systrom brought an innovative idea to life: He enabled people to check into locations, discover new hot spots, create future plans, and earn points by basically drinking. But while he saw value in all the knick-knacks, users didn’t care. It required too many hoops for them to jump through. What they cared about – where and when they perceived value – was in sharing photos that other friends would like. That simple series of actions ­– the intentional sharing and passive yet instant gratification of acknowledgement back – delivered users an emotional and addictive customer experience. That was the singular moment of truth. And value realization, it seems, lay hidden in a much more simplistic experience than Systrom originally thought.

 

With that being said, how can you and your team identify the moment of truth that delivers value realization for customers? And then bring that further up to reduce the amount of time and effort required to recognize value? Here’s a few ways we help our clients do it: 

  1. Apply quantitative and qualitative lenses to your customer journey to determine where moments of truth may lie – not just to convert users into customers, but to drive repeat purchases, upsells, and lifetime satisfaction and value.
  2. Break down quantitative data to uncover moments of customer churn and identify thresholds that transcend customers into advocates and encourage more engaged, continual use.
  3. Interview and engage customers in conversation, both ones who have disengaged and ones who chose to repeat, to outline differences between the consumer groups and identify moments that formed their perceptions.
  4. Artificially manufacture and design moments of value realization that doesn’t necessarily reflect the materialistic product or service, but more importantly, demonstrates the value. Execute competitive analyses to identify opportunities to accelerate time to value.

Create customer experiences and evaluate value delivery from the perspective of the intended customer or end user.

The Bottom Line

Over the years, consumers have grown more differentiating and discriminating about the value they’re receiving and feel less loyal to brands. That means businesses must not only continually improve products and/or services, but truly optimize value realization to occur earlier in the customer journey to maintain wallet share, grow their consumer base, increase customer engagement, and lead the market.

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