What is Customer Data Analytics?
It refers to an accurate view of a company's customer database. This view is helpful to make decisions about how to best achieve and keep future customers. It can also identify high-value clients and recommend methods to engage with them.
Organizations can optimize the customer journey by their buying habits, preferences, behavior, etc.
A huge volume of precise data can provide an accurate analysis. Without this, analysis insights may be completely incorrect and useless.
Based on Mckinsey reports, companies can increase profits by utilizing data analytics reports. This gives an edge over other competitors.
Source; Mckinsey & Company
Customer Analysis helps companies to stay ahead of the curve in customer experience.
You can answer several customer behavior questions with analytics. Such as:
- Who are my 20/80 customers? - Twenty percent of customers generate eighty percent of the revenue.
- What marketing actions correspond to revenues? - The best marketing channel with the least customer acquisition cost ( CAC).
- What do my best customers do? - The industry and any relevant ecosystem they exist in.
- What customer retention actions have the best return on investment( ROI)?
What are the processes of Customer Data Analytics?
Data analysis is a must for a successful marketing strategy. It is a process that involves collecting data from several touchpoints. Companies can use data and demographics to sell their products and services. It also increases engagement and revenue.
What information should a customer data analysis have? The four points listed below are critical for your marketing strategy:
- Determine your current customers
- Check which consumers you are yet to reach.
- Recognize your clients' requirements.
- Check for the factors that influence the purchasing decision of your clients.
The stages of the customer data Analytics process are:
Stage 1 Data Discovery
You should conduct an audit of existing available data before undertaking data discovery. This stage will acquaint you with the data environment. And also allows you to first diagnose, to determine the quality and quantity of data available for analysis.
The audit begins by planning and discussing issues and difficulties with stakeholders.
Opportunities should be finalized and prioritized before the end of the audit.
Stage 2 Exploratory Research
Under this stage, the analysis will give insight into your customer base. As a result, you'll be able to identify patterns among your most profitable customers. The discovery of these clients will aid future analysis.
For example, By studying transactions, you can find seasonal buying trends. This determines where the resources have to be focused.
Segmentation is also an important analysis in this stage. It is the process of identifying client categories and tracking their behavior over time. Segmentation can take place on a variety of levels.
Stage 3 Action
You can set measurable targets once you have basic segmentation in place. Also, you can check how different consumer segments perform.
At this stage, an explanation of these aims will have more relevance because the prior analyses help point out the direction to take.
Stage 4 Prediction
Future prospects appear bright with the consumer data analytics core and evaluations available. With client feedback, you can stay ahead of the competition and meet customer needs.
Benefits of Customer Data Analytics
Decision-making becomes more effective.
Extensive data analysis helps to create long term results. Companies are now looking at data before making decisions.
Data analytics takes a lot of the guesswork out of marketing plans. It determines what material to make, create goods, etc.
With strong data analytics technology, businesses may create prediction models. By doing so, they can stay ahead of the curve.
The marketing channel will improve
Businesses that understand their clients will be able to sell to them more. A variety of sources, including e-commerce and social media, are used to collect data.
The data derived from these resources provide clear guidance. As a result, they may fine-tune marketing techniques for better results.
Improves customer service
Behavioral analysis of consumer data is important for a great service. For Example, a company can use an information model for e-commerce activity. This determines which products to show at the checkout to increase sales.
Data analytics helps firms in saving resources. Data mining can help organizations to meet their needs. The analysis of supplier data can help to identify the causes of production delays. It also helps in determining possible future problems.
For Instance, A vendor is not able to handle the requisite volume during the holiday season. The company may supplement or replace that vendor to avoid production delays.
Accurate campaign ROI measurement
For a long time, attribution has been a major issue in the market.
Advanced analytics tool helps to measure the efficacy of the channel. Such as advertisement, communication, or other user engagement methods.
This knowledge provides a framework for future plans.
For example, A survey before, during, and after the event will provide you with all the information. The decision can then be made to know whether it is worth repeating or not!
Tracking Behavioral changes
Consumers have a lot of options in today's environment. A company that ignores consumer expectations and needs will soon go out of business. In this digital age, users change their opinions when they encounter fresh information.
There is an enormous amount of consumer data. It would be impossible for companies to track behavioral changes without Analytics. Analytics informs you about your market and if there have been any changes.
How do you put customer data analytics into action?
You now understand the processes and benefits of consumer data analytics. Let's look at four methods you can start implementing consumer data analytics now.
Capture customer data
Data collection is the primary focus for businesses. They want enough customer data to analyze for major decision-making. Companies can collect raw data and customer views by using survey forms. Example- SurveyMonkey or Typeform.
For instance, businesses can capture customer acquisition data in the following touchpoints;
- Viewing a demo
- Joining a live webinar
- Submitting the form to get access to gated content
- Clicking on a promoted marketing campaign
- Landing on a website page from an organic search
- Watching explainer video
You can integrate the CRM platforms into websites like Google Analytics. This is helpful to track, site visitor behavior and capture the data for analysis.
A company with a mobile application can collect passive data like user actions, log out, log in and in-app purchase history.
But, capturing massive customer data is not enough, you need the other three stages.
Store collected data
In the age of cloud storage, data warehouses can store your customer data. Most businesses don't need to install their data centers. For website hosting, email, paid ads, cloud-based tools store and retrieve customer data.
Organize data using software
Data sorting is critical for efficient customer data analysis. A customer data platform( CPD) is a marketer-managed system. It collects customer data from all sources and organizes them into profiles for analysis.
Example: Segment, Microsoft Dynamics 365 Customer Insights, SaleForce Interaction Studio, and Oracle Unity.
According to CDP’s Institute, a real customer data platform needs to do the following;
- Create unified profiles for identified individuals
- Share customer data with any system that needs it
- Ingest data from any source
- Respond in real-time to profile requests and new data
- Capture full details of ingested data
- Store data ( subject to privacy constraints)
Analyze data to get insights
Customer analytics is all about getting actionable insights. Companies need to set the desired objectives before analyzing customer data. Some questions customer data analytics can answer include:
- What content ( type, format, distribution channel ) generates more qualified leads?
- Is there a better way to communicate with my customers?
- How can I increase acquisition while reducing Customer Acquisition Costs ( CAC)?
- How can I optimize my messaging, brand positioning, and offering?
- How do I reduce the churn rate and increase the customer retention rate?
- What markets can we double down on?
Features of Customer Data Analytics
It is random experimentation where two or more variables are shown to distinct segments of website visitors. This will result in a version that has the greatest impact on the intended business metrics.
A customer analytics tool with a split-testing feature enables you to test customers in real-time. With this capability, you can do the following;
- Solve customer pain points fast
- Reduce bounce rate
- Improve conversion rate optimization
- Made low-risk site modifications
- Redesign your website to optimize for future conversions.
It is the process of dividing a large user base into groups using common characteristics. Customer segmentation aims to provide customized messages that resonate and convert.
These are the four most common types of market segmentation
Collaboration and Sharing
Consolto’s Rich Communication Center goes beyond building customer relationships. Staff teams can use advanced built-in features to collaborate and share insights.
Key Performance Indicator help companies determine if they are hitting their business objectives. For instance, a business may want to know its customer lifetime value. In order to determine how much it can invest in acquiring new customers.
How Consolto's Mini-CRM analytics can help your business?
CRM analytics software is also known as Customer Analytics. It is the process of analyzing data to uncover important insights that can drive decisions for the company. The goal is to have a deeper understanding of your clients to market products or services to them.
Consolto's CRM analytics is suitable for businesses of all sizes. Especially, if you are a developing corporation with a high volume of leads. The software gathers and tracks prospect interactions and behavior on your website.
It interprets this data and compiles actionable reports. This assists in determining where you should invest your time, money, and resources.
With Consolto's Analytics, you can measure the following
- Quality of your leads
- Quality of email
- Quality of sales and customer service
- Sales performance
Below are the features of Consolto's CRM analytics that can help your business
Demonstrates a clear customer journey
CRM analytics can map out a clear customer path for your company to follow and act on. Every consumer goes through a journey, beginning from awareness, consideration, and brand advocates.
Few buying decisions happen instantly, while some take a longer time. For example, B2B businesses can take a considerable amount of time to invest in a software tool.
When dealing with a lengthy process, it's critical to have software in place. It allows sales and marketing team members to oversee the customer's journey.
Consolto's CRM software can examine the points, where the buying decision may occur in customer journey. Also, it tracks key metrics that a company needs to determine satisfaction rates.
These data points are then evaluated to improve their sales and customer relationship.
Provides information on client retention tactics.
Consolto analytics helps in detecting positive and negative signals based on client activities. Customer complaints and call recordings can reveal if a customer is satisfied or not. Your team can thus respond according to the situation.
It could be customer service or opportunity to cross-sell and up-sell. In any case, studying those signals will provide data that will help meet client needs.
Indicates a change in the status of lead
The transition from disinterested to purchase is one of the major signs of a buyer's journey. Any type of customer transaction mirrors this transition. The Analytics dashboard can be accessed with Consolto.
The dashboard displays metrics of how it is affecting our business.
CRM tracks website visits, social media, and forms, when a company thinks of buying a solution.
The proper analytics will reveal trends among certain customers. Based on the importance and frequency of their contact.
Enables predictive modeling
It is the technique of anticipating outcomes using data. By testing custom data, businesses can predict whether a future project will succeed or fail. To use predictive modeling, a business must have access to as much client data as feasible.
If you analyze 100 client encounters, you will have a lot more insights and information than if you analyze only three. Luckily, Consolto CRM contains all the information you need to unlock those insights.
Last but not least, CRM analytics can assist your company in segmenting clients. Use CRM analytics to group clients based on behaviours such as the customer's role, history etc. In this way, you can better market your goods and sell them to clients.
Consolto CRM is designed with end-users and salespeople in mind. With a clean and simple user interface, 92 percent of our users find it simple to use. The CRM also includes a live video chat and can be readily integrated into any website. Wix, WordPress, and other CMS platforms support the widget.