Thinking Holistic Analytics? Think Verb

4 Ways in Which Verb Brings the Superpowers of Holistic Analytics to Its Clients and Their Customers.


Does the name “Juicero” ring a bell for you?

Well, if it doesn’t, don’t worry. Juicero was launched in 2016 as a WiFi-powered juicing machine for home. Despite being designed by a group of expensive engineers and raising $120 million in funding from the likes of Google Ventures, the product fell flat in the market. Consumers quickly rejected the overpriced and over-engineered juicing solution since it failed to meet their needs in an ergonomic and economical manner.

Unfortunately, the majority of customer dashboard builders today are going the “Juicero” way. They are stuffing dashboards with features that nobody wants and compromising usability at every turn. 

At Verb, we understand and recognize that designing holistic dashboarding solutions requires out-pacing the users’ existing solutions. This is achieved by endowing the new solution with features that the users seek and aspire to have. 

At the same time, eliminating problems and inefficiencies inherent to the current solution is required. We make this happen using a no-code, embedded approach to data visualization that addresses your customers’ needs.

In this blog, we share with you the top 4 features of our self-service customer dashboard builder that will pique your interest in holistic analytics. Before we get into it, we will quickly touch upon our underlying philosophy and principles that make holistic analytics the cornerstone of our solution.


Verb’s Two-pronged Approach to Holistic Analytics

#1 We Begin by Thoroughly Understanding the Data Needs and Decision-Making Requirements of Our Clients and Their Customers

If you have ever watched the master chef of a top-notch restaurant in action, you probably have a fair idea of how much attention they give to getting the right ingredients. 

Similarly, even we start by taking a deep dive into the raw materials – which is nothing but data, in our case. If the data is stale, inaccurate, or uneven, all embedded analytics is doomed to fail, no matter how sophisticated and robust the various components are.

Understanding data and making it analytics-ready is not just the first step, it is mission-critical. This is why we don’t just glaze over it, we actually create an inventory of your customers’ data along with the correct data context. 

Put simply, we find answers to the following questions before moving on to the subsequent steps.

  • What is the volume of data that your customers are working with?
  • How many types of data are they using?
  • From where are these data being sourced?
  • Where do all their data currently reside?
  • To what extent is the data clean, purposeful, and integrated?
  • Is “context” missing for any of the data?
  • Is the “context” embedded within the data and data operations?
  • What are the compliance requirements for various kinds of data currently in use?
  • What are the key data gaps in the customers’ decision-making process?

Arriving at the right answers to the above questions plays a major role in the performance, scalability, cost, and ease of administering customer data dashboards. Hence, it is always a good idea to check beforehand if your dashboarding solution can match the specific data and processing requirements of your customers.

Verb eliminates the need for you to intervene by starting right at the grassroots level. We begin by understanding the data profile of your customers inside out and work our way up from there.

#2 We hit the sweet spot for SaaS Customers by Overcoming Feature Limitations, Cost Overruns, and Self-sufficiency.

Once we have mapped the data landscape, we then move on to developing the best-fit dashboarding solution for your customers.

To do this, we begin by asking ourselves what it is that your customers are truly looking to solve and overcome.

  1. Are they looking for enhanced dashboard capabilities to overcome feature limitations in the current solution?
  2. Are they looking to minimize the cost overruns that they are experiencing with the current solution?
  3. Are they seeking a more self-sufficient ecosystem for analytics, visualization, and decision-making?

It is interesting to note that a customer may even be looking for all three in the new solution. The idea here is to see what is driving their data and decision-making needs and how best it can be addressed in the new solution.

How We Overcome Feature Limitations

Verb overcomes feature limitations by providing a well-stocked library of data visualization templates, with options ranging from conventional to contemporary. These include various kinds of graphs and charts, extensive data filters, integrated and interactive dashboards, appealing dashboard themes including white-labeling options, scheduled report generation, options for optimal refresh rate (day-wise, hour-wise), and so on. 

How We Minimize (and Then Eliminate) Cost Overruns

One of the fundamental ways in which we prevent your customers’ costs from spinning out of control is by eliminating the need for multiple tools across the data analytics lifecycle. With Verb, it’s just one tool that auto-generates meaningful data experiences for your customers.

This also means that your customers won’t have to invest in data warehouses, data pipelines, or engineering man-hours to initiate and maintain the dashboard setup. A costly development stack and a dedicated software development team are simply not required with Verb. All those resources are encapsulated in a single platform that is easy to use, no-code, and scalable. 

Furthermore, Verb has put a cap on the data ingestion limit to customize the data synchronization process to 500 GB. Otherwise, data analysis and visualization would be extremely time-consuming, which would further shoot up overall costs. Implementing this cap also brings down the infrastructure cost.

How We Foster Self-sufficiency in the Embedded Analytics Ecosystem

Verb induces self-sufficiency in the data analytics ecosystem by enabling your customers to create dashboards that can be easily replicated and reused. Since Verb is completely no-code, even non-engineers can build dashboards without any dependency on data engineers for holistic analytics. 

Our data infrastructure is fully automated. Our pre-built data pipeline integrations ingest raw data, normalize structured and unstructured data, and handle advanced multi-tenant architectures by federating distributed schemas. Furthermore, we leverage existing authentication and authorization to create model-bound data segmentation that is centralized and more secure for the purposes of multi-tenant analytics.

Lastly, Verb enables self-sufficiency by going beyond just charts. Users can easily set up, model, and analyze data on a need-basis without any dependency on data engineers or being limited by charts alone.

Top 4 Features That Make Verb a Frontrunner in Holistic Analytics for Customer Data Dashboards

At Verb, we don’t just help your customers visualize their data. We see to it that they experience that aha!’ moment every day through intelligent, contextual, and timely insights that fuel goal-oriented decision-making. 

Holistic analytics is at the core of how we make this happen.

Here are the top 4 out-of-the-box features of Verb that make us the front-runners in holistic analytics for customer data dashboards.

#1 Interactive Analytics Using Tile Action

Great visualizations are simple, intuitive, and purposeful. Data Tiles are an interactive tool for the seamless exploration of data. Our dashboards are populated using data tiles to showcase all your customers’ data in meaningful ways based on the decision-making context.

Based on their applications, data tiles come in various formats. KPI tiles, for example, help to track, benchmark, and compare the key performance indicators of a company, a product, a department, a geographical region, a marketing channel, a project, or a team. Customers can view the relevant KPI metrics as a single number for a single variable, a single number for a group of variables, a trend analysis chart, growth comparisons, or extensive KPI lists.

Visual tiles include X-Y charts (like bars, columns, line charts, and area charts) as well as pie charts and gauges.

Tiles like data tables come in two formats, i.e. standard tables and pivot tables. They allow aggregation of table values, comparisons in table values across time, column filters, conditional formatting, and data pivoting.

Downloadable data tiles enable the end-user to download a report by selecting the displayed button within the collection.

Other types of data tiles include location tiles, specialty tiles, data science tiles, and organization tiles. You can learn more about tile action in Verb here.

#2 No-code Data Transformation, Modeling, and Segmentation

In Verb, the entire experience becomes no-code, automated, and self-service. This holds true even for complex data operations like data transformation, modeling, and segmentation.

Data transformation is a crucial step in harnessing the most out of data by validating it, massaging it, and enhancing it to make it analytics-ready. Most other providers in the market require users to jump through hoops to get this step done. In many cases, non-engineers are dependent on software development teams for data transformation. Verb joins data across multiple sources and transforms the same without any SQL coding and querying by the users. Our interactive features allow users to dive deeper into the data and navigate throughout the system with ease and clarity.

Similarly, modeling the data as per the decision-making context so as to glean the maximum insights is primarily seen as the job of an engineer. It is believed to require advanced knowledge of data models, statistics, and business analytics. Segmenting the data based on the decision-making needs of the users in various roles across the organization is also perceived to be a highly technical job.

However, with Verb, all that becomes a matter of a few clicks, and hence, anyone can do it. Our dashboards come loaded with data transformation options that can be easily accessed. They can then be converted into the desired output streams by anyone familiar with the product using our vast library of analytics modules and data visualization templates. Data modeling and segmentation are simple, automated processes that can be completed with just a few clicks by the user. Since Verb has an elaborate and meticulous user onboarding process that culminates in step-by-step hand-holding, your customers will never be in trouble when dealing with any stage of the analytics lifecycle.

#3 LIVE Data Conversion (Currencies, Time-zones, and Dates)

As the scale and complexity of your customers’ operations increase, they are likely to deal with data operations across borders, time zones, and currencies. This necessitates automated and LIVE data conversion mechanisms within the dashboarding solution so that users don’t have to keep track of dates, time differences, and exchange rates.

Verb delivers all analytics in the currency of the end-users choice. This is referred to as currency conversion. With Verb, you can deliver analytics in the currency of your end-users choosing without building an entirely new solution. There is no need for the data to be input in any particular currency – users can input data in any currency and command Verb to automatically convert it to the currency of their choice.

Instead of presuming the conversion rates, we provide users with the flexibility to manually enter them. Users can also convert the historical amounts into a given currency by augmenting the results. With further integrations, complex business processes can be automated using this feature.

Similarly, all time values are converted to a time zone of the end-users choice. This is referred to as time-zone conversion and saves users the headache of converting time and remembering/looking up differences across various time zones.

Lastly, Verb powers comparison in values like KPI values, table values, trends, etc. across time periods using automated date comparisons. When an end-user culls out any data values across specific dates, Verb automatically uses the dates to enable time-based comparisons like weekly, monthly, quarterly, or yearly comparisons. Users can compare the real-time analysis with the previous time period with just a few clicks since Verb automatically builds queries and compares the data points.

#4 Easy, Quick, and Flexible White Labeling of Dashboards

While many customer dashboard providers stock their library with attractive themes and templates, it is possible that your customers are still unable to find the exact match for their brand. They are looking for the perfect combination of colors and the overall look and feel of the dashboards to reflect the exact brand colors, vibe, and personality.

With Verb, white labeling of dashboards reaches a whole new level since your customers are not limited by the templates we provide. They can select the exact colors that match their brand elements and can implement the new color scheme with just a few clicks.

For example, competing beverage brands like Coke & Pepsi might use similar data sources, data operations, analytics modules, visualization options, and reporting structures. But their charting and reporting elements will reflect their unique brand colors and set them apart from each other. Given how serious most brands are in their branding efforts, we have ensured that complete and no-fuss white labeling is a specialty of Verb.
Keen to explore how our holistic analytics solution for customer data dashboards can help you and your customers?

If you want a tour of our newest features get in touch!