Customer analytics can assist in making simple business decisions such as selecting which advertising platform provides the highest return.
But customer analytics also offer more complex strategies like mapping customer journeys in order to create personalized marketing campaigns.
Customer analytics goes well beyond making smart marketing choices - it has the ability to have a lasting impact on your bottom-line too! According to one study, companies that employ customer analytics intensively report 115% higher ROIs and 93% greater profits.
Customer Analytics Is Important
Here are a few business benefits from various forms of customer analysis:
- Customers experience higher customer satisfaction and retention levels.
- Reduce lead generation costs and acquisition expenses
- Sales and revenue increase.
- Increased User/Customer Engagement With Increased brand recognition comes increased user/customer engagement.
Data provides insights that show you the way to meet every revenue and growth goal - from customer engagement to increasing loyalty - from increasing engagement levels to building customer retention rates.
As is often said: you cannot improve what is not measured!
Due to consumer sophistication and demands, businesses today need more comprehensive data collection methods in order to understand both customers and their requirements effectively.
Successful companies owe much of their success to data. Experts report that firms that utilize customer analytics extensively are three times more likely than their rivals to achieve above-average growth in revenue while experiencing an enhanced return-on-investment (ROI).
Customer analytics provides businesses with valuable answers that benefit every department in their organization, while targeting marketing efforts more precisely and more frequently than before.
Customer journey analytics help your sales team better understand the purchase journey of customers and utilize this knowledge to shorten sales cycles.
Customer analytics can assist your product team in designing an enhanced and more desirable offering by showing which features customers enjoy or dislike most about it.
Customer analytics provide customer service teams with tools they can utilize to reduce churn and predict its occurrence.
Calculating CAC and LTV will provide an indication of where you should start in terms of customer analytics.
These numbers will form the backbone of many customer analytics queries you may be exploring. Take for instance determining where most of your advertising budget should go: it wont do just to base this decision off how many customers came through one channel -- such as Facebook; having an expensive CAC and low LTV could prove counter-productive in this instance.
What Can Customer Analytics Do For You?
As soon as you start collecting and analyzing customer data, use it to answer queries and make business decisions.
For instance, use it to discover ways of:
- Personalizing content and products, both individually or collectively.
- Delivering messages at just the right moment
- Customize your campaigns according to who your desired target is.
- Maintain positive customer experiences throughout their customer journey
- Help with product creation and marketing strategies.
As well as data from different sources and buy-in from numerous teams, to fully create the picture it takes a centralized view of customers which customer experience platforms can provide.
Customer Analytics: The Four Main Categories
These four categories of customer analytics are illustrated with examples.
- Descriptive Analytics. Gives you insight into past customer behavior. (For example: 30% of customers returned product X a month after purchase).
- Diagnostic Analytics. It helps you to understand "why" customers behave the way they do. Example: 50% of customers believe that product X was not what they expected.
- Predictive Analytics. You can predict future customer behavior..
- Prescriptive Analytics. It gives you suggestions for how to influence or change customer behavior. (For example: Online ads and social media campaigns can increase product X sales by 25 percent).
All types of customer analytics fall into one of four categories.
Customer Analytics: 6 Types That Are Useful
- Customer Journey Analytics
- Customer Experience Analytics
- Customer engagement analytics
- Customer lifetime analytics
- Customer loyalty and retention analysis
- Voice of Customer Analytics
1. Customer Journey Analytics
Customer analytics refers to any form of analysis which analyzes interactions between your brand and customers - from initial research they conduct on its products or services right up until purchase decision is finalized.
Your data points may come from various interactions and sources; organic and non-organic visits to product pages provide insights into early stages of customer journey - information gathering and research; while cart abandonment rate indicates how many shoppers abandon their carts before actually purchasing anything from you.
Consider which metrics you could employ in evaluating customer journey steps which you deem essential to your business.
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2. Customer Experience Analytics
Customer experience analytics provide valuable insight into customer sentiment for any brand, with metrics including usage rates and time to benefit being key metrics in providing support services (for instance through tracking support tickets or emails or live chat.
To make sense of it all a platform designed specifically to collect these statistics will give access to customer support metrics).
CSAT scores are one aspect of customer experience. CSAT surveys measure customer satisfaction with your services (think diagnostic analytics).
CSAT surveys can easily be administered via email or software after key events like training or purchases; furthermore they allow you to assess and optimize the onboarding process.
Analysis such as customer effort scores can also provide valuable insight into customer experiences.
Paying close attention to qualitative data can also be of critical importance. When customers contact you with complaints via email or other methods, respond appropriately before recording it in an Excel spreadsheet (or another suitable format).
Create reports highlighting similar complaints received to identify what action will best serve your clients and customers.
3. Customer Engagement Analytics
Customer Engagement analytics fall into two broad categories, specifically product/service engagement analytics and brand/company engagement analytics - Web analytics is also considered customer engagement data.
Customer success teams can monitor user engagement with your product. Engagement marketing, however, goes beyond usage metrics; it also involves exploring and shaping customer relations for maximum brand impact.
As an example, you could segment website users and monitor how they engage with content, calls-to-action and navigation paths on your site.
Once segmented, target them with customized ads or emails targeted toward these interactions based on click-through rates or social media engagement metrics that give insight into customer retention strategies.
Customer engagement should be central at every point in a customer journey; thus, two types of analytics will likely overlap.
4. Customer Loyalty And Retention Analysis
Analysis that measures customer loyalty can tell you whether customers prefer you over competitors. Repeat buyers and churn rates can tell us whether customers trust in what your business provides them with or not.
These metrics provide insight into why some customers might prefer you over another business.
NPS (Net Promoter Score) surveys are one of the most frequently employed ways of measuring loyalty, asking respondents the "would you recommend this product or service to a friend" question.
Our Ultimate Guide for NPS surveys can assist your company if this approach sounds interesting!
Customer retention and churn are other metrics which can indicate potential future problems; when combined with customer satisfaction metrics they provide an effective means of designing proactive programs to boost customer retention.
5. Customer Lifetime Analytics
Customer life cycle encompasses multiple components that encompass customer journey and experience analysis, but an essential metric in this analysis is Customer Lifetime Value; this measure provides information about revenue you expect to generate over time from any given customer relationship.
Calculating this metric depends heavily upon your business model. Consulting services may be helpful in discovering an approach that best fits for your firm; otherwise it could simply involve multiplying average retention rate with average purchases and product by average deal value to get to this number.
There are more accurate ways of calculating this metric; one such approach would be segmenting customers based on type.
Doing this allows you to quickly identify those customers most worthy of receiving expensive marketing campaigns and which should receive those investments first.
CLTV can help inform decision-making in various ways. If it appears to be declining, this may indicate problems with repeat customers; or if marketing and acquisition campaigns costing more than anticipated may indicate overspending.
6. Voice of Customer Analytics
Voice of the Customer should be self-explanatory: what your customers say matters for your business and these analytics allow you to capture their opinions, preferences and expectations.
Voice of Customer Analytics includes CSAT/NPS surveys, social media interactions/posts and anything that allows you to listen in on what your customers have to say.
Utilize best practices when conducting customer interviews - pose pertinent questions to test knowledge about demographics as you gain an in-depth view into them all.
Read More: Artificial Intelligence for Customer Service
Customer Analytics Tools
You can use these tools to collect and analyze customer data.
Purchase
A platform for customer engagement, allows you to centrally store all customer interactions - such as those found through live chats, websites, social media and chatbots - into one centralized hub.
It also tracks any actions taken by your team (e.g. Responding quickly to customer questions helps identify more effective means of serving your clients).
Kissmetrics
Kissmetrics enables you to understand user behavior across all pages on your website, such as which elements lead to more conversions and so forth.
IBM Watson Customer Experience Analytics
IBM Watson Customer Experience Analytics helps you visualize the customer journey and analyze it.
Google Analytics
Google is a well-known search engine. GA offers a wide range of tools for measuring traffic, website behavior and attribution.
Hootsuite
Hootsuite Analytics helps you track your social media performance to get valuable insights into future campaigns.
Hotjar
Hotjar lets you analyze web traffic behavior using tools such as heatmaps, recordings and more.
Customer Analytics: Best Practices
You should:
- View customer interactions through an omnichannel perspective. There are software programs that provide a single view of the customer, but its important to also consider data from other sources.
- Pay attention to qualitative data. Some customers are very open with their opinions and this makes it easy to identify problems and solutions. Do not ignore any voice from a customer, whether it is a response to your CSATs (Customer Satisfaction Surveys) or an email thats proactive.
- Test solutions and make predictions. Make active predictions, and test different solutions. You may have to test out different options, especially when it comes down to customer engagement.
How To Store And Collect Customer Analytics Data
To get the most out of customer analytics, you must collect and store customer data.
Data Collection
Beginning is essential; your team may utilize various marketing tools like Google Analytics for this task. Google Analytics tracks visitors behaviors on your website.
No comprehensive list could possibly enumerate all of the tools in this category - Google Analytics being one such instance.
These tools may provide some insights into your customers, but are usually insufficient; to gain full advantage, add three additional pieces.
Sorting Data
Sort your data so it can be sent directly for analysis, Segment is an ideal customer data platform (CDP) to help with this.
Your CDP serves as the traffic director, telling your data where and when it needs to go.
The CDP was developed to connect various tools within an organization and ensure that data collected by them is standardized across your enterprise.
Standardized data thats under tracking control makes sorting and analyzing easier than non-standardized, unstructured information.
Data Storage
Data warehouses provide an ideal place for the CDP to send its information, making customer analysis much more effective.
Data warehouses collect and organize large volumes of information from numerous sources - websites, apps, emails and cloud applications among them.
Redshift is our go-to storage option; however we also offer BigQuery and Postgres databases.
An effective data warehouse will keep all your customer-related data in one central place for easy analysis purposes.
Data Analysis
Your data analysis process must also be effective and efficient.
Most often, this process can be accomplished using business intelligence software like Mode Analytics or Tableau, however these solutions do require knowledge of SQL to use effectively - Chartio can also be an ideal alternative if this is something new to you!
Once your calculations are in, its time to dig further with customer analytics and answer more specific queries:
What Source Of Acquisition Results In The Highest LTV Value?
This question will allow you to determine where the money of your business should be best spent; by allocating additional spending or decreasing spending.
Youll have an idea where additional expenditure should take place as well as where cuts might need to occur.
Data should come from two sources - your website analytics tool and payment processor.
Assuming your customers coming through one promotion are giving a higher lifetime value, and customers coming from Facebook provide even higher LTV.
Should that be the case for your company, invest more heavily into Facebook customers.
How To Improve Your Business With Customer Analytics
We will now introduce to you the most important ways to improve customer analytics and to build a strong relationship with your clients using all of these consumer behavior insights:
Via Your Customer Personality:
A good and valuable study of their customers will help them to understand more about them, classify them according to behavior and personality, and develop a positive approach in management.
This will also assist them with building a marketing strategy that is based on the consumers actual needs.
Better Customers Experience:
Your customers retention rate is based on the experience they have with your company. This includes the internal or online experience, as well as your social media audience.
Your customers satisfaction is important for a successful business and to attract new opportunities.
All The Data Collected Can Be Used To Benefit:
Customer analytics allows you to gain a deeper understanding of the behaviors of your customers with data and insights that are extraordinary.
This data and insight must be incorporated into all your products, future plans and investments, as well as all your customer-facing offers.
Advance Your Decision-Making:
You can improve your brand awareness, engagement with customers, sales and revenue by analyzing your customer data.
Update Your Results After Comparing And Analyzing The Results.
Customer analytics is important, but its more important to analyze the data, and use that to create a timely advertising plan.
However, you must update your customer analytics regularly to reflect any changes in consumer needs and company growth.
What Is The Most Common Customer Experience?
Answering this question will allow you to gain a clearer picture of how visitors become customers and gain invaluable knowledge that will improve your marketing tactics.
You will require data from multiple sources in order to address this query, since customer journey encompasses any interactions your potential customers may have with your business, from emails providers and website analytics tools through to sales tools and beyond.
Your customers may contact support prior to becoming customers, and making it easier for customers to access support early could make the customer acquisition process smoother and simpler for all involved.
Be proactive by having your support team reach out as soon as they start their trial period!
Is There Any Time Of The Year When Our Ltv To Cac Ratio Is Higher Than Usual?
Your LTV to CAC ratio could have an enormous effect on how your company spends its advertising funds, especially marketing budget allocation.
Why? If it exceeds 3:1, that indicates an underinvestment that could allow faster growth - increase marketing budget allocation during any specific month when this occurs and your LTV/CAC ratio surpasses 3:1!
To effectively answer this question, two things will need to be known in order to provide an answer: your customers can be divided up by month when they became customers; as well as total marketing and sale expenses per month.
As seen above, this company discovered that their LTV:CAC ratio was greater in April compared to either January or February, giving them insight into how best to allocate marketing and advertising dollars more effectively.
What Are The Behaviors That Lead To Higher Retention Rates?
Answering this question should not be difficult and can promote positive behaviors by providing an answer.
Assemble data from various sources; CRM development solution, email marketing platforms or website analytics solutions could all provide necessary input.
Heres an example of a music-playing app where researchers discovered that users who favorited at least three songs were more likely to stick around for longer.
Assuming you were employed at a music app and discovered this figure, if this statistic concerned your job you might examine how to increase user adoption by persuading more to add three songs as favorites.
What Are The Top Features That Our Customers Like?
Although knowing which features your customers like can be useful, focusing on those which your most loyal ones enjoy can be even more so.
By asking this question you can determine which are most valuable and therefore, which features should be developed next. In addition to that it helps determine how best to structure customer onboarding so customers get access to useful tools as soon as possible.
To answer that question, you will require data about customer behavior from your product.
Do some investigation and discover why your top customers are so frequently using your data export feature, then create new features to make this process simpler for customers.
To answer all these queries accurately and comprehensively, data warehouses were established. Business Intelligence (BI) tools can help analyze information stored within them - this would otherwise take weeks or even months!
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Customer Analytics Helps You To Understand Your Customers
Todays most successful brands understand customer analytics in depth. If you want your business to deliver superior service to its customers, invest in a customer analytics platform now! Customer analytics can have a profound effect on your bottom line.
In conclusion, leveraging customer analytics is crucial for businesses aiming to improve customer service. By harnessing the power of data, companies can gain valuable insights into customer behavior, preferences, and needs.
This enables businesses to make informed decisions and tailor their offerings to meet customer expectations.
By analyzing customer data, Customer software development companies can identify patterns and trends, allowing them to predict customer needs and proactively address issues.
This leads to enhanced customer satisfaction and loyalty, as businesses are able to anticipate and fulfill customer requirements effectively.
Moreover, customer analytics can help businesses identify areas of improvement within their customer service operations.
By analyzing customer feedback and interactions, companies can identify pain points and streamline their processes to deliver a seamless and personalized experience.
Additionally, customer analytics enables businesses to segment their customer base and target specific audiences.
This personalized approach allows companies to tailor their marketing and communication efforts, resulting in more impactful and relevant interactions with customers.
Ultimately, leveraging customer analytics empowers businesses to better understand and serve their customers, resulting in improved customer service, increased customer loyalty, and ultimately, a competitive edge in the market.
Embracing customer analytics as a strategic tool is essential for businesses looking to thrive in todays customer-centric landscape.
