Data is a critical component of a successful ABM strategy. How can you leverage data-driven insights for effective marketing?
Designing a winning ABM strategy begins with market research, understanding your prospects and their buying patterns, and aligning sales and marketing teams to pursue the accounts. In this article, we have compiled resources to help you utilize data-driven insights to enhance the performance of ABM campaigns and achieve the desired outcomes.
Accelerating ABM with data
The success of ABM is paramount, with the tailored messages and personalized customer experience. And without data-driven insights, it can be challenging to hit the mark. The secret to accelerating the performance of ABM programs is to use the right database. A data-driven ABM approach will enable you to understand your best prospects and curate campaigns that resonate with them. An ABM program driven by data helps to launch a fast, effective start and makes it convenient to identify high-performing content.
Gathering and analyzing customer data is an essential ingredient of ABM’s targeted approach. You need current and accurate data to evaluate relevant target accounts, their pain points, preferences, and needs. You can procure relevant information using various routes, such as surveys, customer interactions (emails, cold calls, social media channels), and website analytics. The goal is to find out whether the target accounts resonate with your offerings and how you can tailor campaigns to win their interest.
Optimizing data
In the digital age, when information is abundant, you need to strategically use data to optimize the buyer’s journey. There are three steps to accomplish this:
Prepare the Data
The first step is consolidating information from all corners of your business. Bring all the data in one place and clean them to get a clear overview.
Enrich Data
You can enrich existing data by adding unique data points to get clarity about the customers. The more you know about them, the easier it gets to curate personalized campaigns.
Conduct Market research
Utilize data visualization tools to identify the segments where your strengths lie and where you have scope for growth. It also helps align sales and marketing teams to pursue the target accounts. Without a shared understanding between these departments, discrepancies may arise while utilizing organized data and implementing personalized ABM initiatives.
Data-driven insights for Targeting specific accounts
Precise targeting is the highlighting feature of data-driven ABM. When you identify the pain points and ideal solutions of prospects, you can personalize messages that help build strong customer-brand relationships. Categorize the data into segments, making it easier to identify the accounts you want to target first.
Implementing Predictive analytics
Analyze customer data using relevant information and statistical algorithms to understand the future outcomes of customer behavior. Predictive analytics can be utilized to identify the ideal customers for your business based on the data collected, including historic buying patterns. It saves time you would rather invest on accounts less likely to respond.
Segment data for ideal profiles
ABM allows account targeting and segmentation to divide potential accounts into groups based on relevant characteristics aligned with the brand’s goals. These are some types of data that can be used for account segmentation and targeting, such as demographic, behavioral, and customer feedback.
Demographic: gives an overview of the characteristics of the customers within the target accounts, including age, gender, designation, location, etc.
Behavioral: looks into the buying patterns of the target account segments, their actions, and interactions with a company’s offerings. You can utilize this information to understand their purchase history.
Feedback from customers: this can be a valuable resource to improve ABM by identifying the key accounts interested in the brand’s offerings and the decision-makers.
Integrate ABM customer base into sales and marketing data
Combine customer information for an ABM campaign with data outsourced from other marketing and sales efforts. This would give you a holistic view of the campaign performance by providing an idea of its impact on the sales and marketing efforts. The integration allows you to understand how the campaign impacts their efforts, thereby allowing informed decision-making. For instance, if a brand is launching an ABM campaign to target a specific group of accounts, they can learn how these prospects interact with other marketing initiatives like email campaigns, webinars, etc.
Wrapping it up
For your ABM strategy to be effective, the target-specific database must be robust. You need to know your ideal prospects at a deeper level. And one way to achieve this is through data-driven ABM insights. While incorporating such information, identify the key metrics important to your brand like customer lifetime value, acquisition cost, and retention rate. Then, using a CRM system you can track and analyse them. The data can be utilized to create customer segments based on shared characteristics. You can utilize this data to deliver personalized messages and design customized campaigns. These can be launched on social media channels frequented by the prospects.
Microsoft’s outage disrupted many industries, stating our reliance on technology. How deadly was this blue screen to companies worldwide?
A recent worldwide IT shutdown caused by a defective update shocked essential services around the globe, emphasizing our reliance on technology and the possible risks of software malfunctions and security breaches. The disturbance started on a Friday morning and impacted various sectors, including airlines, banks, and healthcare systems.
Domino Effect of The Blue Screen of Death
The culprit was a malfunctioning update to CrowdStrike Falcon Sensor, an antivirus program commonly integrated with Microsoft products. While not a cyberattack, the incident demonstrates the cascading impact software glitches can have on global operations.
A wide range of Microsoft services were impacted, including:
It took Microsoft roughly six hours to publicly acknowledge the outage. Since then, the company has likely identified and addressed the underlying cause. Their focus is now on the complete restoration of services and user support.
It took Microsoft roughly six hours to publicly acknowledge the outage. Since then, the company has likely identified and addressed the underlying cause. Their focus is now on the complete restoration of services and user support.
Lessons Learned: Vulnerability and Prevention
This incident serves as a stark reminder of two key points:
Our Dependence on Technology: Modern society is deeply reliant on technology, and disruptions like this can have significant consequences.
Vulnerability in Interconnected Systems: The interconnectedness of systems creates vulnerabilities. A seemingly minor issue in one program can have a rippling effect across entire industries.
The investigations continue, and the companies are eager to understand the exact cause of the CrowdStrike update failure. It will be crucial to implement preventative measures to avoid similar disruptions in the future.
If anything, the outage is a testimony to our reliance on these technologies that have become a part of our lives, and it is nearly impossible to live without them. Even after the massive losses the companies incurred, they cannot stop using the tools that caused it. Why? Because of the trust built over the years and the lack of better alternatives.
The question arises, is your team ready with a contingency plan in these unforeseen circumstances? Did you nearly escape the blue screen of death, or were you able to keep its hands far away from your throat?
Digital Asset Management (DAM): Benefits, Features, Use Cases
All aspects of business operations are transforming into digital, and data is no exception. How can you use DAM software to improve performance efficiency?
Given the flux of digital technologies, managing and organizing digital assets, such as documents, images, videos, and media files, has become a top priority. Digital asset management is the need of the hour. It helps businesses of all sizes seamlessly manage various types of online data.
With this system, you can streamline workflows and maintain brand consistency. It’s like a centralized place to access various media assets of a company. One of the core features of a DAM solution is to optimize the production of rich media, especially within the sales and marketing sectors. What’s more— it can help you establish brand consistency through automatic asset updates and reinforcement of brand guidelines.
Digital Asset Management: Key Benefits
Effective digital asset management is a must-have due to the various benefits it offers:
Reduced production costs
Asset centralization within a DAM system enables organizations to find and reuse assets, reducing production costs and duplicate workstreams. The resulting efficiency helps to bring assets and solutions to the market faster.
Improves organizational transparency
When you implement a DAM system, you experience a clear and comprehensive view of digital assets. In this way, it helps you positively impact management, content planning, and execution. If you are looking for better collaboration among various stakeholders, then DAM software can help you accomplish this goal. It eliminates redundant projects, thus introducing impactful workstreams.
More lead conversion and customer retention
The chances of customer retention are high when you deliver a personalized experience. And with DAM, it gets easy to accomplish this. You can launch relevant marketing materials at the right time to enhance customer engagement. This can accelerate the buying cycle and nurture strong customer relationships with your brand. When there is more customer satisfaction, they are likely to convert into paying accounts and possibly come back for your products/services.
Improved brand consistency
While creating digital materials, be it webinar content, videos, or images, it is important to maintain consistency and align with the brand’s voice. When you use DAM software, it creates consistency across all messaging, visual representation, and other means of brand adherence. Moreover, it allows functional areas and business units to reuse creative files and other assets for conveying the same voice to the market. DAM solutions protect brand identity, irrespective of the teams that share the digital data. By maintaining consistency, it simplifies brand management and the delivery of a positive customer experience.
Better compliance
You cannot deny that it is essential to comply with licenses, legal documentation, archives, and other assets that are important for meeting industry-driven regulatory compliance requirements. This applies to industries of all domains and sizes. With improved compliance, you can easily organize and rapidly retrieve digital materials, which saves you time and resources. DAM also makes sure that your sales and marketing teams utilize only digital assets they have usage rights on.
Increased Content Value
Incorporating a digital management solution allows you to streamline your content strategy, delivering high value throughout the asset lifecycle. With this system, you can swiftly find, organize, or repurpose the existing content. Your sales and marketing teams can easily share digital files, which increases brand reach.
Boosts productivity
Since DAM seamlessly aligns the marketing teams, strategy, and digital assets. It allows you to invest more time towards asset creation, thereby increasing productivity. With better performance efficiency, customer engagement is also likely to improve.
Steps involved in the application of DAM Software
When using digital asset management software, these steps will enable successful implementation:
1. Creating the asset
The first step of the DAM process involves creating and preparing different multimedia files using standardized templates and formats. Standardization helps to easily capture, recognize, and sort out documents for simplifying search and data retrieval.
2. Encoding and indexing
The next step is to work on the metadata— descriptive information added to the assets for context. It is an essential ingredient of the DAM process, helping with indexing—the process of systematically cataloging and organizing digital assets that makes asset search easier.
3. Implementing workflows
In the third step of using the DAM system, you integrate digital assets into relevant workflows, projects, or processes. You can link them to specific tasks, projects, or campaigns. By this stage, you have already assigned metadata and completed the indexing. Now, you can apply task and process automation to streamline DAM.
4. Version control
B2B businesses are dynamic, where the data is in a state of flux. Given such circumstances, companies may experience a regular inflow and outflow of resources and restructuring. Version control helps to update the data that is continuously changing. With this feature, you can ensure that the digital assets you utilize are up-to-date. It allows you to keep tabs on the changes, revisions, and data updates. This applies to the multiple versions or iterations of a digital asset.
5. Governance through permissions
In this step of the DAM process, focus on establishing policies, procedures, and guidelines. With each of these deliverables, you can govern the creation, use, management, and lifecycle of digital assets. This will allow you to authorize personnel and conserve resources from unauthorized use, corruption, or loss.
The Key Functions of DAM Software
When you integrate a digital asset management solution, it helps you organize, store, and retrieve different digital files seamlessly. From creating and redistributing assets to archiving, reusing, and retiring, these solutions go through a lifecycle of digital assets. Let’s take a closer look at these:
Create Digital Assets: Some DAM tools may come with built-in image and video editing features that fast-track the asset creation process.
Edit & Review: A digital asset management solution makes it easy to collaborate with built-in tools for commenting, annotation, and version control. This function allows multiple users to share feedback and suggestions on the same asset.
Integrations: DAM offers users the flexibility to integrate with other tools like content management systems and project management platforms.
Distribution: Integration of DAM allows you to effectively manage the distribution of finalized assets along with other tools like content management systems or social media platforms.
Tracking and archiving: After a project is completed, DAM solutions ensure that your assets are organized as per the categories, such as date, metadata tags, or file type.
Safe storage: These solutions can safeguard digital assets from unauthorized access or modification. You can achieve this by setting user permissions and roles and implementing encryption for an extra layer of protection.
Data search and retrieval: When the files are archived, you can access tools for organizing, indexing, and searching digital assets. Some of these include AI-powered search functionality.
DAM: Use Cases
Businesses across various domains utilize digital assets for the benefits they offer. Let’s take a look at some of the use cases of this software in the tech domain:
Your management department can use digital asset management for delivering systematic records and streamlining operations such as talent acquisitions and payroll receipts.
Your sales and marketing teams can utilize this software for better brand management.
When the access control depends on the business unit, functional department, or designation, DAM allows you to control access to digital data.
Integrating DAM into your business
You can seamlessly integrate DAM systems into your project management software, image editing software, productivity tools, distribution platforms, and other tools. Since all data assets are now digital, you can almost instantly access the files. Moreover, the production of new marketing materials can be accelerated due to its easy integration. Sales and marketing teams can quickly access approved content and utilize it for social media channels or marketing campaigns.
Summing up
With the world going digital, data and assets such as media files, images, and documents are also being stored online. Digital assets eliminate the hassle of disorganized or incorrect information. If you want to deliver brand consistency while maintaining high productivity, digital assets are your go-to solution. An effective digital asset management software comprises features that enable management of access control to digital data. Having up-to-date assets is simplified with DAM, which allows sales and marketing teams to instantly access and share information directly from the platform. Incorporate DAM throughout the buyer’s journey and experience seamless data management.
Shortening the sales cycle is among the top priorities for sales teams. How can analyzing your sales pipeline help you reach the conversion stage faster?
Performing a sales pipeline analysis is beneficial if you want to increase sales. It works even if you are satisfied with your current sales performance. But what exactly is a sales pipeline analysis, and what is its importance?
Analyzing the sales pipeline involves examining leads to understand their status and progress. In this blog, we explain the importance of conducting a sales pipeline analysis and list six top sales pipeline metrics to monitor.
What is sales pipeline analysis?
Sales pipeline analysis helps you examine your sales pipeline to understand what is happening with your leads and why.
What does sales pipeline analysis tell you?
Analyzing the sales pipeline provides crucial insights into your potential customers. What prompts the leads who convert to do so? What causes those who do not stay? Out of the two options, which one occurs more frequently?
How you choose to carry out your analysis is totally in your hands, but it is often beneficial to examine different key performance indicators (KPIs) to understand the impact of your efforts.
Why conduct a sales pipeline analysis?
Conducting a sales analysis is important because it lets you understand how to enhance your sales strategy. It demonstrates your strengths, enabling you to replicate those accomplishments in the future. Similarly, it also reveals the areas of weakness in your sales, such as where leads are being lost.
Utilizing data from sales pipeline metrics to adjust the entire sales process can lead to consistent growth in sales numbers, resulting in a progressively higher ROI.
Six sales pipeline metrics to track and analyze
We have previously highlighted the importance of monitoring various pipeline KPIs to effectively conduct a sales analysis, but which specific KPIs should be tracked?
Here are six key performance indicators to examine in the sales pipeline.
Rate of conversion at each stage
Your conversion rate indicates the percentage of leads that turn into conversions. Naturally, the term “convert” has various interpretations. At the beginning of the sales process, it could just involve subscribing to your newsletter. However, ultimately, it translates to the lead buying something.
It means you need to analyze your conversion rate individually for every step in the process. Monitoring the conversion rate lets you pinpoint where you are losing the majority of leads. Having a high conversion rate at the end of the funnel but a low one at the start implies that your top-of-funnel sales process requires improvement.
Duration of sales cycle
The length of your sales cycle reflects the average duration of a sales cycle or the time it takes for the average customer to move from the start to the finish of the pipeline.
The more time spent in the pipeline, the higher the likelihood of dropping out before making a sale. Furthermore, the more time it takes for potential customers to move along the sales process, the slower your income will come in.
Speed of sales pipeline
The velocity of sales pipeline progress is linked to the length of the sales cycle. Instead of tracking lead retention in the pipeline, it focuses on the speed of revenue generation within it.
To figure it out, simply multiply the total deals in the pipeline by the average deal size, then divide by the average duration of the sales cycle.
This metric is advantageous for the same purpose as the length of the sales cycle – it shows the speed and effectiveness of your sales pipeline in generating revenue for you.
Customer acquisition cost (CAC)
CAC is an average cost measurement to earn a new customer. To determine your CAC metric, add up all your marketing and sales expenses over a specific time frame and divide by the total number of new customers acquired in that period.
It provides an idea of your expenses related to your sales pipeline. If your Customer Acquisition Cost is excessively high, you are spending way too much, or your sales strategies are yielding very unsatisfactory outcomes. In any case, you should focus on adjusting the ratio to benefit you.
Churn rate
Another vital factor to pay attention to is the customer retention rate. The churn rate is essentially a metric that indicates the portion of your potential and existing customers you no longer have within a specified time frame. To find it, divide the customers lost by the initial number of customers for that period, then multiply by 100.
It’s probably needless to mention that the higher your churn rate, the more negative impact it has on your situation. A high churn rate indicates that something in the later stages of your process is causing people initially interested to leave, so your task is to determine the cause.
Net promoter score (NPS)
NPS is a measure of customer satisfaction. It just evaluates the level of satisfaction your customers have towards your company. Survey your customers to determine your NPS by asking how probable they are to endorse your business, rating on a scale from 1 to 10.
A high NPS signifies satisfaction among customers for your company, while a low NPS suggests significant potential for enhancement. If your Net Promoter Score is not meeting your expectations, ensure to also inquire with your customers about how they believe you can enhance it. Next, apply those enhancements to boost your NPS score.
Wrapping it up
Understanding and efficiently controlling your sales pipeline will result in notable enhancements in your results – this is something we can all agree upon now. The sales team gains from the sales pipeline and aids in overall team achievements as long as the entire organization is in sync with revenue objectives. Businesses that achieve sales targets understand the importance of effectively managing the sales pipeline to track a prospect’s progress through each stage of the sales process, enabling them to nurture leads and increase conversions.
How to Use Data Analytics to Improve Customer Experience
A good CX can bring you closer to your brand advocates. How can data analytics help you deliver a seamless experience?
Customer experience is what connects your brand to your customers. It is a bridge between brands and their brand advocates that can be defined as the way a consumer perceives your brand. Every interaction your customer has with your brand has the potential to either weaken or strengthen the bond and having an optimized website or a good SDR is just the starting point for providing a positive customer experience.
Good CX involves building relationships by understanding what people want, need, and value. The complete experience includes pre-purchase associations with the brand (via marketing or awareness), the process of researching and making the purchase (either in-store or online), and post-purchase interactions (regarding service, repairs, extras, and more). The goal is to build meaningful connections between the brand and the customer.
Now that we know how customer experience affects our brand, let us understand how data analytics can help us optimize it.
What is data analytics for customer experience?
Analyzing data from customer interactions can give you a lot of valuable insights. You can get a clear idea of customer satisfaction, loyalty, and other metrics that reflect how your customers interact with your product.
You can also utilize data analytics to improve customer experience and overall improve customer satisfaction — thus increasing customer retention in the long term.
Importance of using data analytics for customer experience
Customer experience analytics is obligatory for companies that want to prioritize their customers. It lets companies understand their customers’ journeys, helping them to personalize experiences to meet individual tastes. By interpreting customer behavior, businesses can target their offerings better.
Also, customer experience analytics helps specify pain points in the customer journey. It motivates businesses to proactively resolve issues, resulting in higher customer satisfaction and less customer churn. Predictive analytics also plays a role in strategic planning by foretelling future customer behavior.
Customer experience analytics is a vital factor in driving customer loyalty, growing conversion rates, and enabling business growth.
Steps for analyzing customer data with customer experience analytics
Here’s the 5-step technique you can follow to get the best results of your customer experience analytics:
Decide your goal
Compile customer data
Visualize collected data
Select an analytics process
Employ the insights
Let’s take a closer look at each of these measures below!
Decide your goal
Before you even begin to collect data or look at customer experience analytics, you must first extrapolate what you’re trying to identify. You must set SMART goals to ensure that you understand the data points that reflect customer needs and business goals.
Collect customer data
When analyzing customer experience data, you will typically consider two main types of feedback: direct and indirect.
Direct customer feedback – Direct customer feedback consists of metrics like:
Net Promoter Score (NPS)
Customer Satisfaction Score (CSAT)
Customer Effort Score (CES)
Voice of the Customer (VoC)
These are the CX analytics that most product marketers think about as they offer a direct understandings of customer behavior. Direct customer feedback could also comprise responses you receive on social media or comments from feedback surveys.
Indirect customer feedback – Rather than monitoring behavior, indirect customer feedback is influenced by customer behavior. This includes metrics like:
Average Handle Time (AHT)
Customer Lifetime Value (LTV)
Average spend
Customer churn rate
Customer renewal rate
Whenever you calculate the LTV, you get an indirect look at how delighted customers are with your product (since they wouldn’t continue paying for a flawed solution, much less upgrade their subscription). Other ways to accumulate indirect customer feedback include social listening, customer review monitoring, and analyzing voice chat transcripts.
These data points may not be as direct as NPS or CSAT scores, but they’ll help you drill down on the business outcomes that result from the customer experience.
Visualize collected data with different dashboards.
Once you have gathered data on customer satisfaction scores, lifetime value, and churn rates, then it is time to visualize everything using different dashboards.
Choose an analytics method and analyze customer data.
There are various data analytics solutions and procedures that you can use to filter through your customer analytics insights. Each process has pros and cons, so you must be acquainted with the options available to you. A few different analytics processes to consider include:
Descriptive analytics. Descriptive analytics uses real-time and historical data to spot trends and the relationships between certain metrics.
Diagnostic analytics. Diagnostic analytics uses data to understand why certain events occurred, whether a rise in churn rates, a reduction in lifetime value, or other shifts in the makeup of your SaaS business.
Predictive analytics. Predictive analytics uses models and algorithms to forecast future performance or the probability of certain outcomes.
Prescriptive analytics. Prescriptive analytics uses data to figure out what the best course of action is and make decisions based on multiple factors.
Which one you go with will ultimately depend on the data you collect, which insights you expect to gather, and the business outcomes you are trying to achieve. For instance, predictive analytics is often adequate for businesses attempting to decrease risk or lower costs.
Use the insights to improve customer experience.
Finally, it is time to use your conclusions to improve the customer experience. Remember, collecting and analyzing data is only beneficial if you utilize those insights to make everlasting, favorable changes to your product.
Collecting customer journey analytics but never making changes to the onboarding process or customer engagement strategy would be a total waste of time. As such, you should proactively fix negative patterns you recognize and double down on the features that get new customers in the door.
Conclusion
CX is quintessential to sustaining customers, and various industries are placing importance on data analytics to better comprehend customer behavior, preferences, and needs. You can use this information to create better products and services. Data analytics can help you improve the customer experience by reducing friction, personalizing the journey, and adapting your marketing based on the needs of your users. So, if you thought data analytics was required only for those marketing campaigns, it is time to rethink your strategies!
Understanding clients and their buyer’s journey is a total game-changer for your business. How can you select the best tools to provide reliable insights?
The sales and marketing teams of every B2B brand invest so much time and effort in building the target customer base. It can be exhausting to find the right combination of platforms to gather client data. A range of customer analytics platforms to evaluate the information will direct insights from users and interpret their responses. As you browse through these, you probably realize it can be challenging to find reliable information.
We’ve curated a list of the ten best customer analytics software options to help you understand your buyers more deeply. You’ll learn how these tools work, how to combine them, and how they can help you make informed business decisions and achieve your goals. Learning how these platforms function and how to implement them for good decision-making can bring you closer to your goals.
Let’s dive in!
What are customer analytics tools?
Simply put, customer analytics are metrics that enable you to gather valuable data about your target audience, evaluate them, and visualize them as graphs, charts, etc. With these platforms, you can collect and analyze customer data, thereby gaining insights into their behavior, preferences, and motivations. They help you look into customer segmentation, sentiment analysis, and personalized marketing. You can accomplish this using various features, including issue analytics, lifecycle optimization, real-time Support Vector Classification (SVC), and AI-powered health scoring. Your customer service teams can utilize customer analytics tools to employ advanced data techniques for informed decision-making to drive business growth.
Top 10 Customer Analytics Tools
For businesses, customer data is a precious resource. Keeping up with the trending tools will save hours spent on downloading information and looking closely at every customer interaction. It’s quite cumbersome!
We’ve curated a list of the best platforms to help you through the journey of customer analysis. When you are familiar with each of these and their key features, you can select the right tool for your brand.
1. Google Analytics
(Source: Google Analytics)
One of the most popular analytics platforms, offering you extensive website assessment capabilities. The best part is— it’s free! Since it requires no cost, it is popular among businesses worldwide. With Google Analytics, you can track customer behavior from their actions, such as clicks or site visits. The reports created in this platform will enable you to understand your customers and their needs with marketing results.
Let us take a look at other striking features of this customer analytics tool-
Traffic analysis– enables you to get a complete overview of the audience journeys. You can also optimize channels like social media or websites having high traffic.
Segmentation- this feature categorizes customers and website visitors into segments, making it easier for you to understand the engagement.
2. Zendesk
(Source: Zendesk)
Sorting through data can be overwhelming; Zendesk simplifies things for you. The charts and spreadsheets can be analyzed in a matter of minutes. You no longer need to fret about handling massive volumes of data to filter what you need. Zendesk allows you to blend data from multiple sources, such as email, chat, or social media, into a single dashboard that can be analyzed and compared seamlessly. It is the best tool for optimizing customer service. With Zendesk, you no longer struggle with reporting due to its capability to fine-tune and deliver customer insights accurately.
There are Zendex integrations- applications that can be connected to the Zendex platform for elaborating its functionality, automation, and enhancing efficiency. The integrations can be one or two ways. In a 1-way Zendesk integration, data can be synced from an external product to the tool or vice-versa, but not both ways. If you want to swap data both ways, you will require a 2-way integration.
3. Sprout Social
(Source: Sprout Social)
This customer analytics tool is ideal when you want to evaluate engagement on social media channels. It can manage large volumes of responses. The additional features such as automating urgent concerns and alerts for high activity, make it a good go-to platform for managing social media responses. Like other metrics, this also offers performance tracking, with the added feature of distinguishing between paid and organic reach. This platform simplifies the process of going through data swiftly, giving an idea to choose the best time to upload posts.
Thus, with Sprout Social, you can amplify your marketing efforts seamlessly.
4. Kissmetrics
(Source: Kissmetrics)
To increase brand visibility, your sales and marketing teams are probably going to great lengths. Launching events may be one of them. This cloud-based customer engagement solution is a must-have if you want to analyze event performance. Some features of a Kissmetrics platform include in-depth and accurate sales funnel reports outlining the buyer’s journey throughout the sales cycle.
Knowledge of these helps to discover the gap areas to enhance engagement and consumer experience. A key characteristic of Kissmetrics is to segment users as per variables like demographics or actions. This information can be collated from a specific segment to create a comprehensive analysis report. So, you have all the valuable data to help you understand your audience, and build a better relationship and brand credibility.
5. UXCam
(Source: UXCam)
It’s a product analytics software that gives optimized insights on mobile devices. Some features of UXCam that stand out include retention analytics, issue analytics, and dashboards. Let’s walk through each of these:
Retention analytics– UXCam can sort through customer databases to help you understand the key actions that lead to retention.
Crash analytics– You receive alerts as and when crashes happen without wasting time.
Dashboards– present a report that gives an overview of performance engagement and scope for improvement.
6. Mixpanel
(Source: Mixpanel)
What makes Mixpanel different is its in-app product engagement analytics for web-based and mobile applications
Key features:
Engagement analysis– overview of customer engagement with a comprehensive report
Impact analysis– Whether it’s a new release or updates with a large dataset, measuring the impacts helps you understand customer response.
Reporting– What’s best about the Mixpanel tool is it lets you mix different metrics on the dashboard and visualize the data as reports.
7. Treasure Data
(Source: Treasure Data)
If you are struggling with a complex data-related issue, then Treasure Data must be your go-to analytics. It is integrated with the customer data platform, making it reliable for predicting critical insights based on customer feedback. A striking feature is its real-time Support Vector Classification (SVC) dashboard. This provides a quick insight into customer profiles, segmentation, behavioral patterns, and other metrics.
8. Tableau
(Source: Tableau)
Its specialty lies in visualizing data and integrating AI. With Tableau, you can access real-time visual analytics, promoting actionable insights. The best part is— There is no coding required. The built-in AI and ML take customer analytics tools a notch higher. You can generate AI-driven reports to support informed decision-making for business growth. What’s more— you can create dashboards using its library of pre-built dashboards. Once created, these can be shared through cloud networks, promoting the exchange of industry-specific dashboards.
9. Hotjar
(Source: Hotjar)
There are two striking features of Hotjar analytics: heatmaps and session recordings. With heatmaps, you can extract qualitative data on user behaviors. It lets you observe the elements of your brand that the users like the most. The scroll maps feature integrated with this feature allows you to assess the scroll patterns of customers. Once you know this valuable information, you can effectively design marketing campaigns.
With the session recordings, you can dive into user actions and not just that. You can also connect them with impactful actions that provide qualitative data.
Apart from these, the Hotjar analytics also comes with a funnel feature that collects data on every interaction with your brand. This includes all interactions throughout the sales cycle. When you get these insights, you can depict how many users converted into paying accounts and how many didn’t follow through. Such valuable data can help build on the gaps and grow customer engagement.
10. Gainsight
(Source: Gainsight)
The features of this customer analytics platform remain robust due to three pillars: Customer Success (CS), Product Experience (PX), and Digital Hub (DH). CS provides customer feedback analysis, and when clubbed with NLP (natural language processing), you can get an idea of actionable insights. The striking trait of Gainsight is the AI-powered playbooks curated to customer challenges. The AI integration can detect possibilities and recommend the right action plan. It also has a health scoring component that predicts customer expansion and renewals. The added advantage allows brands to focus on accounts with a higher score and improve their experience.
11. Salesforce
(Source: Salesforce)
This customer relationship management software will be an asset for your sales teams. The CRM analytics of Salesforce are compatible with different devices. You can utilize its AI integration that comes with augmented analytics, thus promoting automated workflows. The built-in actions menu is the highlighting feature, enabling decision-making without leaving the portal. You can conveniently schedule meetings, update campaigns, and so on.
12. CleverTap
(Source: Clevertap)
Understanding customer data is possible with a wide range of metrics. But what about getting an idea about their buying pattern? That’s where CleverTap comes into the picture. It sends billions of notifications in one day, offering you trend and pattern recognition features. It also has a lifecycle optimization feature that smoothens your interactions with customers throughout the buyer’s journey.
13. CRM Creatio
(Source: CRM Creatio)
If you are looking for an innovative customer relationship platform, this is the perfect choice. With CRM Creatio, you can streamline and enhance various responsibilities effortlessly.
And the best part is— it is applicable to companies of all sizes and domains. Its key features are data visualization and workflow optimization, made simple with a process modeling tool. A CRM Creatio offers multi-channel marketing, improving performance engagement.
14. Amplitude
(Source: Amplitude)
Coming to Amplitude—specializing in analytics for buyers’ journeys and the customers who convert into leads. This platform enables brands to evaluate user actions, thus supporting data-driven decisions.
Any action that customers take related to your offering is termed an event. And for most businesses, events are the main objective of using Amplitude. It helps you get a complete overview of user engagement clicks, likes, follows, etc. This analytics offers five default events to which you can add events and analyze customer response. The standout of this customer analytics tool is event segmentation, a feature that promotes analysis of events and gives an idea of what the audience prefers. You can run simple to complex analyses and view reports in an easy-to-interpret manner. The thing to note here is that dashboards are restricted to Amplitude users.
15. InMoment
(Source: InMoment)
It’s an AI-driven platform to enhance customer experience that is best fitted for analyzing feedback.
Here’s a brief overview of this customer experience analytics tool:
Conversational intelligence– gathers data from different information sources and creates a report to give an overview of customer experiences.
Engagement engine– incorporates AI to engage in personalized communication with customers, promoting a more valuable response.
Rounding off
Customer analytics tools provide valuable insights about your target audience. It’s like the pinnacle of customer retention and a flourishing sales funnel. The expertise of these tools helps brands dive into user engagement and provide valuable feedback. When you incorporate the right analytics, it becomes easier to segment customers based on criteria such as demographic, location, device, etc. Overall, the standout feature of customer assessment is path analysis, which allows you to visualize the actions taken by the customers while engaging with your offerings.
When you acquire data on customer insights, it also helps to optimize the buyer’s journey. If you can track the user behavior through each phase of the sales cycle, it enables you to address any gaps in the sales funnel. Similarly, monitoring the retention rates is a valuable insight for your business for estimating brand growth and reach. If you can promptly respond to changing customer behavior patterns, it would give you a cutting edge in the competitive market. The list of these customer analytics platforms will help you accomplish this goal swiftly.
