Category: root cause analysis

Dynamic KPIs, Saving Filters as Groups, Updates to Root Cause Analysis and More – Explorazor Product Updates January 2023

by adminin Brand Managers, CPG, Data Exploration, Explorazor product updates, root cause analysis

We’re rapidly developing Explorazor to help Brand Managers conduct fast and efficient data exploration. Having already launched seamless root cause analysis, conditional formatting, dual and triple-axis charts in November’s release, we have made some other improvements this time around.

If you are yet to be acquainted with Explorazor, it is a CPG and pharma-specific data exploration tool laying the groundwork for skilled professionals to focus on solving real market problems instead of grappling with unstandardized data and slow laptops all the time. 

The Explorazor proposal for Brand Managers is to work on a harmonized dataset, accessible to all, facilitating instant data pivot extraction (via simple querying) and root cause analysis (via simple clicks) – saving time and effort while accelerating hypothesis testing rates. We do model and engineer your data for you as well.

Let’s look at January’s updates:

  1. Dynamic KPI creation

Users can get custom KPIs created as per their requirement, which are dynamically calculated for every query 

Let’s take an example of ‘Rate of Sales’ as a dynamically created KPI:

Simply insert ‘Rate of Sales’ as a keyword in your query as shown below:

The above image is an example of a dynamically created keyword. Users can get custom KPIs such as Rate of Sales, Market Share, etc. created as per their requirements.

It’s dynamic, so the query will be relevant all the time. As per your query, your numbers of the KPI will be calculated and updated in real-time. For example, you can get KPIs like ‘market share’ which can be calculated dynamically for brands, geography, or distribution, using the keyword, you can use the resulting table to create all kinds of visuals for presentation purposes, and/or perform root cause analysis on it.

  1. Filter Grouping

The rationale is simple – managers use a particular set of filters frequently. Typing in these set of filters repeatedly for every query is undesirable. 

Filter Grouping, as you’re smart enough to figure out by now, allows you to save a group of filters under a common header, and use it to apply the group of filters with ease in the future. Simply recall the header the next time you want to use that set of filters.

  1. Updates to Root Cause Analysis

Explore the root cause analysis/drill-down in detail in the linked blog. 

We have introduced more interactive elements to root cause analysis this time. To show important metrics for a data field, directly click on that field to display all its corresponding values in the left panel. 

This will be better understood with an example:

For any field you click, the numbers on the left panel change dynamically to reflect metrics for our area of interest.

An additional convenience here is the ability to sort the information on an ascending or descending basis. 

Some Other Updates

  1. Recently used keywords will now be prompted as suggestions as you type for quick access. A Google-like feature, and when it comes to a search interface, there’s no reason not to have it Google-like
  2. Min & Max query support is live
  3. There’s an option to edit live data connection options
  4. Updates to conditional formatting

That’s it for this time, and we’ll be back with more updates next month. Our goal remains the same: to help Brand Managers in CPG and Pharma focus only and only on data exploration, and create real impacts through it, with the ultimate objective of improving brand and company revenue. 


Explorazor is a product of vPhrase Analytics.

Take an Interactive Product Tour of Explorazor Today!

product tour

Data Consolidation – The Need of the Hour for Brand & Sales Teams

by adminin data consolidation, Excel, Explorazor, root cause analysis

In this blog, we’ll be highlighting some issues that Brand & Sales teams face with data on a daily basis, and making a case for how data consolidation can remedy these core issues:

So Many Data Sources, So Little Time

Brand & Sales teams deal with so many different datasets at a time: there’s primary sales, secondary sales, MS Value, Media Spends, Research Data from Kantar, Nielsen, or IQVIA, depending on the industry; and more. 

To manage the plethora of data, professionals mainly use Excel. The research we conducted at vPhrase, interviewing 100+ experienced industry professionals, validated many of our hypotheses when we initially started out developing Explorazor, the data exploration tool designed especially for frictionless data exploration. Some of these hypotheses were:

  1. Managers use Excel by default – without any additional support

Excel has become one of the constants of life – all operations are conducted on Excel, without any other tool to even support or augment it. Power BI does extend some value, but it’s meant for dashboards and not exploration.  

To think of replacing Excel was not even in the minds of the professionals we interviewed.

  1. Excel is great – but it does pose some problems

For what man, walking the face of this earth, can deny Excel’s greatness? Shakespearean passions aside, Excel is THE standard for a reason – it facilitates data analysis, holds enormous datasets, enables pivot extraction, conditional formatting and n other functions.

However, we believe that there is an easier way for Brand Managers to conduct data exploration and analysis, without leaving Excel entirely.

As such, we spoke about it with Senior Managers – they agreed that while Excel is the go-to for all number crunching, insight extraction and strategy formation, having to work on multiple datasets means more time consumption and manual work. Laptops process data slowly as compared to a cloud server, which also contributes to time consumption. Furthermore, due to fragmented data storage, managers often have to rely on Insights teams for ad-hoc analysis and crucial insights, something they would rather prefer to live without.

After validating both our hypotheses, we presented Explorazor to our audience – and asked them to gauge one central benefit that Explorazor provides:

Data Consolidation – The Answer To Many of Excel’s Drawbacks

Explorazor is a data exploration tool that lets users conduct queries, obtain data pivots, and conduct root cause analysis via point-and-click, on an INTEGRATED, CONSOLIDATED dataset. There are various industry terminologies going around, like data stitching, data consolidation, unifying datasets, combining datasets, etc., all refer to the same thing. The Explorazor team cleans, standardizes, and combines the datasets for a single-platform usage through Explorazor.

A clarification here: Explorazor complements Excel, and does not replace it.

An Integrated or Consolidated Dataset Means 

  1. Better correlation between data points

Your primary sales is doing good, but your call average has actually been declining since COVID. Such data correlation is easily obtained on platforms like Explorazor. 

Similarly, Dolo made huge sales during the pandemic, but it actually sold more due to HCP recommendations and ad campaigns, rather than calling and field sales efforts. Now that the pandemic has receded, it comes to light that the rural areas have largely been ignored and a sizable chunk of sales comes only from select urban areas.  

Such data exploration and correlation is much easier on an integrated dataset.

  1. Better root cause analysis

We’ve written a separate blog just covering this point. Explorazor helps users arrive at the ACTUAL root cause of events, because users can conduct drill-down and drill-across on the entire data at a time. 

It’s all about better decision-making.

  1. Time and Effort Efficiency 

Managers spend more time testing hypotheses and conducting ad-hoc analysis independently, without having to revert to Insights Teams. Explorazor lightens the laptop burden of processing huge datasets by storing data on server, accessible via browser. 

An Integrated or Consolidated Dataset Also Means 

  • Faster analysis, faster laptops
  • Better, and easier analysis
  • Greater Independence for Brand Managers
  • Greater space for Insights Teams to focus on long-term strategies
  • A space for users have ready access to required datasets
  • A space for users to collaborate on projects
  • A data-driven work culture
  • Greater revenue 

Take an Interactive Product tour of Explorazor!

PRODUCT TOUR