Author: admin

In Retail, Building the Right Omnichannel Strategy is Everything

by adminin Customers, Explorazor, Omnichannel, Retail, sales

Let’s look at the retail landscape today and how important an omnichannel strategy can prove to be in efficiently marketing a brand and driving revenues.

THE NEED FOR AN OMNICHANNEL STRATEGY:

As many times as you have read it, the truth stands that the pandemic initially forced customers to shop online, and in time, customers adopted digital services big-time. This is evidenced by the fact that a whopping 20 million people in Southeast Asia alone converted to being digital customers in the first half of the year 2021. Online searches for terms like ‘instant delivery’ have shot up by 215% in India, just 2021 to 2022. 

The conclusion is that customers today are digitally present, and experience content and brands across so many touchpoints, that it is mandatory to have an omnichannel strategy in place for your brand.

An omnichannel strategy is a cohesive sales and marketing approach that seeks to use every customer touchpoint to provide a consistent and effective customer experience. It involves offering a company’s products & services at all customer touchpoints. Such touchpoints include digital channels like web and app, physical, brick-and-mortar experiences, and any other platform or device that a customer accesses.

‘Effective customer experience’ here means that a customer is satisfied with the product and/or while the company simultaneously generates revenue from that activity. 

2 WAYS AN OMNICHANNEL STRATEGY HELPS COMPANIES:

  1. Increased customer satisfaction – and company revenue

Let’s understand the power of omnichannel strategy in achieving customer satisfaction while simultaneously increasing revenue. 

Consider the example of Petco Health and Wellness, an American pet retailer selling pet food, products, and providing related services. During the pandemic, it understood that its competition and other third-party online retailers were not able to fulfill orders within time. Petco introduced ship-from-store options where customers could browse and purchase online, and pick up the same from physical stores nearest to them. 

Petco met the customers where they were, and provided a key micro-service that made customers love them – and made them some money. Petco’s acquisition costs were cut down by two-thirds, and they recorded a 100% year-on-year increase in sales.

  1. High CLV and retention rates 

Once sold to, they need to be retained. If you’re wondering who ‘they’ are, you’re probably working too late and need some sleep.

Back to the point. Once sold to, customers need to be retained. Creating an omnichannel presence, or being ‘omnipresent’ lets customers interact with your brand wherever and whenever they choose to. It lets the customers dictate what they want the brand to do, and brands can use this opportunity to foster real-time customer engagement and create lifetime value for the customers. 

We’ve covered the ‘how to do it’ in a related blog ‘Getting Omnichannel Right in Retail‘, but just factor in what you’ve read till now and the fact that the global e-commerce share of retail sales is expected to increase to a staggering 24% by 2026, and you’ll see that there’s no doubt that the companies absolutely need an omnichannel retail strategy.

SOME PREREQUISITES FOR BUILDING AN OMNICHANNEL STRATEGY:

Before you go about building an omnichannel presence, here are some of the things you need to have in place. Keep in mind that the list is more exhaustive, and below points are indicative of the nature of preparation you need to undertake. 

We can also help you with one of the rather important points..stick till the end.

  1. Creating/Mapping Customer Journeys 

When managers and teams work to create a framework for understanding customer journeys and how they react in certain recurring situations, for example, a festival that comes along every year, they are able to understand what the customer wants, and provide it to them. 

  1. Knowing who you are targeting

Let’s get this point through with an example. Think With Google shared crucial information for marketers wanting to reach audiences in Indonesia in the month of Ramadan. The data divided customers into 5 segments:

  1. The devoted prayer
  2. The homemaker 
  3. The Ramadan groomer 
  4. The tech followers, and 
  5. The home-comer

With almost the entirety of Indonesia following the religion of Islam, access to such data proves invaluable when slicing the total audience according to the right kind of demographics.

  1. Knowing what you what to communicate

Once you have the right audience figured out, taking the right message to them is equally important. Create a crystal clear overarching brand positioning that you want to reach to reach your audience with

  1. Conducting quick data analysis 

Driving real-time sales and delivering personalized CX in an industry where customers display volatile, or easily influenced, behavioral patterns requires lightning-fast data analysis. And this is where we believe we can help companies.

KICKSTART YOUR OMNICHANNEL STRATEGY WITH …

In the quest to deliver a standard, unified experience to customers, we’re proposing that you work on a standardized, unified dataset as the starting point of your omnichannel strategy. Our data exploration tool Explorazor is built specifically to help brand teams arrive at high-quality insights in an easier and faster manner than their current mode of working, which is primarily on Excel. The usage is very simple – query the integrated dataset using standard keywords such as ‘MS Value’ for Market Share Value and get instant data pivots. 

Explorazor is also infused with seamless root cause analysis, where managers can identify areas/events of concern via simple double-clicks. Other features such as pivots being downloadable as CSV files, various customizable options and chart style settings, time-period recognition (which is not present in BI Tools such as Power BI and Tableau) make data analysis so much easier, faster, and better for managers.

There’s no reinventing the wheel – one doesn’t have to completely leave Excel to use Explorazor either. Explorazor simply simplifies work done on Excel, to frame it as such. 

Multiple Brand Managers from Fortune 500 love Explorazor. As one of them shared his opinion with us “Explorazor is a more intelligent Excel to me”.  

Start with Explorazor, and end with more effective omnichannel strategies, optimized media spends, and higher revenues. Contact us at support@vphrase.com for a free trial and/or connect with our solutions consultant for a free demo.

Take an Interactive Product tour of Explorazor

Product tour

Interested in Becoming a Brand Manager? Know your IQVIA Data!

by adminin Brand Managers, data pivots, Explorazor, IQVIA, pharmaceutical, prescription, sales data

This blog aims to introduce budding Brand Managers to IQVIA and some of its data columns, to help them understand how IQVIA data helps Brand Managers in the pharmaceutical industry achieve their objectives. 

IQVIA, as its official website introduces, ‘is a leading global provider of advanced analytics, technology solutions and clinical research services to the life sciences industry dedicated to creating intelligent connections that deliver unique innovations and actionable insights’. We have also written similar articles on Kantar and Nielsen data, which you can find in our blog section.

Brand Managers in the pharmaceutical industry use IQVIA data to develop innovative strategies and drive brand sales and adoption. As we mentioned in a similar blog ‘Know Your Nielsen Data’ becoming a Brand Manager requires superior data handling skills and a pragmatic approach to data, where one can arrive at high-quality, real-life conclusions looking at hard numbers.

Just a word: Explorazor is supporting Brand Managers big-time with respect to analyzing their data. More on that later. And yes, Explorazor differs from Power BI.

IQVIA helps Brand Managers in the pharma industry:

  • Take decisions regarding brand expansion and advise ways how they can go about doing it, like analyzing growth potential, evaluating pipelines, understanding risk-opportunity ratio, the investment landscape, and more 
  • Adhere to market requirements, identify regulations, licenses, valuations and any potential market hurdle that may arise
  • Address customer needs better, by sharing information on the market behavior, competition’s performance, customer psychology and behavior, and even mapping a customer’s purchase journey
  • Achieve brand differentiation through timely delivery of evidence-based insights from across the globe. IQVIA’s competitive tracking processes cover and share information from more than 75 markets worldwide
  • Other ways that IQVIA data helps Brand Managers include risk evaluation and mitigation, networking with experts across clinical functions and obtaining intel & tracking of 45,000+ drug profiles and 10,000+ drugs

SOME DATASETS THAT BRAND MANAGERS DEAL WITH – IQVIA DATA

1. Sales Data

As with all other industries, the first thing that a Brand Manager in the pharmaceutical industry will look at is the performance of their Brand in the market, thereby referring to the sales data. There are 3 components to the IQVIA sales data:

  1. Sales Value
  2. Sales Volume
  3. Market Share

This sales data received from IQVIA is already classified geography-wise and product-wise as prescribed by the company.

2. Prescription Data

  1. Prescriptions Count

These are the total number of prescriptions via doctors recorded for a product

  1. Prescriptions per doctor (P/D)

 P/D refers to the avg. numbers of prescriptions for a brand.  It is captured specialty-wise, for example, General Physicians, Diabetologists, Oncologists, etc., and bifurcated on a Zonal level. The P/D ratio lets you know about the key specialties that contribute to the sales of your brand in the market.

3. Supply Chain Manager

From the manufacturer to the wholesaler to the final chemist or the outlet location, this dataset helps Brand Managers track end-to-end product flows. Logistics is a highly lucrative industry in and of itself if done right, and such datasets hold massive monetary implications for the company. It also helps the company be available where customers need them, where the market is thriving, or where there’s a gap to be exploited

4. Longitudinal Patient Data (LPD)

LPD data provides pharmaceutical companies with an understanding of disease treatment and how General Physicians are prescribing cures for them. This helps in new product development, as well as the evolution of current products in the portfolio. Another strong benefit of such a dataset is realized when formulating effective sales strategies for the on-field reps. 

There are many such datasets that Brand Managers work on. But here’s an important point:

DATA IS ONLY AS GOOD AS ITS LEVERAGE

We see from the above points that data literally can potentially impact everything – sales, customer service, supply chain infrastructure, competitive environment, etc.  What’s left is to

  1. Extract the best possible insights from it 
  2. In the minimum time possible 
  3. Another key element is to extract a higher number of high-quality insights from data within the same time frame.

Explorazor by vPhrase helps Brand Managers do all of the above. 

LEVERAGE DATA OPTIMALLY USING EXPLORAZOR 

Instead of multiple files from different data sources, the company’s own data sets, etc. what Brand Managers can do is simply choose to view a single, all-inclusive/integrated dataset on Explorazor, query it via simple keywords, and receive data pivots – at their fingertips.

Let’s just put some of the benefits in pointers, for easy reading:

  • The dataset is standardized, so manual labor is saved there 
  • One can start using Explorazor within the day, so there are no hiccups in adoption
  • Due to the integrated dataset, the extracted insights are high-quality
  • The lightweight design interface is custom-built to deliver speedy responses
  • All of this culminates in a Brand Manager wanting to dive deep and test out more hypotheses than before 
  • Speaking of deep dive, Explorazor also supports drill-down and drill-across into a particular data point. Simple click-and-dig, that’s all. See the image below

Some additional benefits: 

  • Tables can be converted to charts, graphs, and multiple other handsome-looking visuals (did we say handsome instead of beautiful? Oh well!)
  • Any data pivot can be transported to Excel by downloading it as a CSV
  • Any data pivot can be pinned to the ‘Dashboard’ for easy viewing 
  • In-project collaboration with team is possible via tagging/assigning of activities

And most important of all,

Custom made for Brand Managers, and that too primarily in FMCG and pharma. Of all the designations, we chose to dedicate our skills to help Brand Managers ease their daily activities, ironing out many data-related inconveniences they face. Explorazor continues to develop and provide a niche solution for Brand Managers.

Explrazor is a product of vPhrase Analytics. If you want to try out Explorazor for yourself, contact us at support@vphrase.com. It’s free, and it’s fun.

Take an Interactive Product Tour of Explorazor.

Product tour

Interested in Becoming a Brand Manager? Know Your Kantar Data!

by adminin Brand Managers, Data Exploration, Explorazor, Kantar, Uncategorized

As part of our 3-blog series to educate professionals wanting to become Brand Managers, we’ll be introducing you to some columns within the Kantar data that Brand Managers receive, and interact with, on a regular basis. 

The other two blogs in the series are:

For now, let’s look at some columns in the Kantar data and their brief explanations. We’ll be continuously updating this blog as well as the Nielsen blog over time, so be sure to bookmark and check them out once in a while!

 Let’s begin:

DATASETS THAT BRAND MANAGERS DEAL WITH – KANTAR DATA

  1. Households  

Households (HH) indicates the total number of households in the target market. This informs the Brand Manager of the total market potential that his/her brand can ideally target and reach

  1. Penetration 

Household Penetration is the number of households in which a brand is being used. Large brands such as Coca-Cola and Maggi rely heavily on increasing the HH penetration of their products. For this, they develop increasingly robust logistical networks, especially in high-potential countries like India where the majority of the population resides in rural areas. This data point also helps decide the allocation of billions of dollars of investment into advertising and promotions.

  1. Volume 

Vol, or Volume, is the total sales made. Volume could be sliced and analyzed, for example, in a particular time period or for a particular geography. This, of course, is one of the cornerstone data columns needed for progress – What are my sales figures? Which were my highest-selling areas? Which areas showed degrowth? are the fundamental questions that every Brand Manager starts with

EXPLORAZOR – FOR OBTAINING THE FUNDAMENTAL ANSWERS, FAST

Our data exploration tool, Explorazor, is built solely for Brand Managers to obtain answers from data at accelerated speeds. How? Brand Managers view a single, combined dataset on Explorazor, which they query using simple keywords, and obtain data pivots instantly. No switching between files at all.

You can view the 3 Types of Analysis Brand Managers can Perform Super-Easily on Explorazor.

BMs are also able to drill down and drill across to arrive at event root-cause, conduct ad-hoc analysis (independently, without support from Insights teams), and test out more hypotheses than ever before. There’s so much more to Explorazor as it plays its part in complementing Excel perfectly, so users do not have to leave Excel entirely, yet do away with some of Excel’s ‘rougher edges’, if we might call them that.

  1. Volume share

Volume share is the part of the market your brand has captured as against the total category share. This is a broad metric that lets a Brand Manager understand where s/he stands with respect to competition. Necessary remedial/preventive steps can then be taken to overtake the competition and increase the volume share, be it hiring more on-field forces or a from a completely different angle, say, increasing media spends to raise brand awareness in specific regions.

Explorazor again comes in handy when it allows Brand Managers to get all their queries answered at a single place, in addition to drill-down into a particular metric via simple clicks. 

  1. Avg Trip Size

The average trip size is understood as the average number of units bought by a consumer at one time/ in a single go. It is also understood as the average purchase weight per transaction. Since packet weights vary, a Brand Manager can potentially decide on a standardized purchase weight, which can be translated into how many packets of that particular weight were sold to a shopper during his/her visit.

With data on average trip size, a Brand Manager understands the distribution and stocking requirements of a particular store.

SIMPLIFYING DATA ANALYSIS – AND NOT JUST KANTAR

We hope these 5 points gave you a glimpse into the areas that Kantar data focuses on, and how Brand Managers can use these data points to elevate all aspects of their brand, like goodwill and sales. We want to further elaborate on how Explorazor can help Brand Managers achieve all of this in an extremely simplified manner.  

Explorazor holds all the datasets that a Brand Manager works on, and showcases them as a single integrated, standardized dataset on its interface. This includes all the separate Kantar columns we discussed, Nielsen data columns, IQVIA (in case of pharma), primary sales, secondary sales, market research, etc. 

Brand Managers pose queries, and data pivots are generated instantly. This speeds up the data analysis process, allowing Brand Managers to spend more time on strategizing and contemplation instead of conducting the manual labor of standardizing columns and querying multiple data sheets for a single insight. The data pivot on Explorazor can also be customized to produce visually appealing charts and graphs, and exported as CSV as needed.

We are on a quest to help Brand Managers ease their day-to-day data exploration process, relieve them of unwanted manual work and over-dependence on BI/Insights teams, enable them to conduct ad-hoc analysis and hypothesis testing at speed, and ultimately help them arrive at quality, target-smashing decisions.


Also understand how Explorazor differs from Power BI.

Take an Interactive Product Tour of Explorazor!

Product tour

How Kantar Data Helps Brand Managers in the CPG Industry

by adminin Brand Managers, CPG, CPG, Kantar dataLeave a Comment on How Kantar Data Helps Brand Managers in the CPG Industry

We’ll be exploring how Kantar data helps Brand Managers execute their responsibilities and take their brands to the next level. As the company’s official website introduces, Kantar ‘is the world’s leading data, insights and consulting company, helping clients understand people and inspire growth’. Kantar provides data on about 75 local and global markets, covering industries like CPG, Automotive & Mobility, Life Sciences, Retail, Media, Technology & Telecoms, and more.

Let us explore specifically how Kantar data helps Brand Managers, using the CPG industry as an example:

1. Understanding Markets, and Shoppers

Kantar data helps Brand Managers understand the complex purchase patterns of customers, both physical and virtual, in competing categories. It informs them of who is buying the brand and who isn’t. Kantar data also helps BMs understand the overall shopping trends and how competition operates.

Kantar’s specialty lies in:
– Their massive tracking system which captures the shopping decisions of 4,50,000 consumers all over the world
– Smart segmentation that unveils the best growth opportunities
– Competitor activity benchmarking, and
– Tracking behavioral and other types of trends over long periods

2. Growing the Brand and Extending to Newer Categories

Understanding what kind of buyers to target, the feasibility of entering new categories, based on the ability to satisfy what the consumer wants is another way Kantar data helps BMs. Consider also these points:

– Optimizing in-store ROIs via promotion, merchandising, etc.
– Influencing online shopper behavior by devising the right media and marketing mix components
– Hammering down the brand positioning and using existing insights as well as non-data analysis to model the brand structure, to drive sales
– Delving into category based on evidence that provides a futuristic perspective of shopper, category, and retail behavior

3. Driving Innovation

This is related to the classical 4Ps of marketing – how do you innovate your product? What promotional and pricing strategies do you use to sell it at scale? What kind of launch and distribution strategies are best?
Additionally, Brand Managers can use Kantar data to also delve into
– The impact that this innovation will have on the master brand and the brand architecture
– Ways to create the all-important ‘5th P’ – Packaging, for customer attraction
– Ways to optimize the brand portfolio and architecture, and
– Testing and development of concepts, products, and packs

4. Optimizing Investments

Data under this header relates to marketing and retail investment management for optimal returns. It studies
– The best way to conduct advertising spends
– Different digital contexts, examining them to see what works best
– Various touchpoint analyses, their impact and how to improve going ahead
– Various solutions used to drive sales and enhance field efficiencies

The Possibilities are Many

As we mentioned in the very first sentence, Brand Managers in the CPG industry can use Kantar data to take their brands to the next level. The data is there, and that is one part of two. The second falls upon Brand Managers to embark on an exploration journey where they truly analyze the plethora of information in front of them and carve out exceptional insights that serve as action points for the brand’s growth.

If Only Time was in Abundance

It seems heavy, but breaking it down to the simplest of factors tells us that Brand Managers simply do not have the time to conduct such in-depth exploration. This is due to the fact that such data comes in the form of loads of separate files, which are hard to simultaneously, and speedily, manage. Had Brand Managers the time for data exploration, the resulting insights and the subsequent impact of these insights on the brand would have been positively different.

We’ve Got a Present for You

At the risk of sounding cheesy, it’s the gift of time.

Explorazor gets the basics right – all of it. This data exploration tool combines all datasets, including Kantar, so BMs can query on an integrated dataset and receive instant data pivots.

There’s so much more on offer, as we’ve mentioned in other blogs such as ‘Interested in Becoming a Brand Manager? Know Your Nielsen Data!’.
Just read the conclusion, which starts with the header ‘SEPARATE FILE FOR EACH, OR JUST 1 INTEGRATED DATASET?’

Our pursuit is to help you use Kantar data to the fullest. See how, over a demo call.

Take an Interactive Product Tour of Explorazor!

PRODUCT TOUR

Interested in Becoming a Brand Manager? Know Your Nielsen Data!

by adminin Brand ManagerLeave a Comment on Interested in Becoming a Brand Manager? Know Your Nielsen Data!

If you are interested in becoming a Brand Manager and want to learn more about the kind of datasets Brand Managers deal with on a daily basis, you have landed at the right place. We also plan to introduce you to a tool that is currently making the life of Brand Managers so much easier than before. How? Well, keep reading!

We have written similar blogs for Kantar and IQVIA datasets as well, so open both in new tabs and explore them once you’re through this one.

Brand Managers are champions. They are multi-taskers, owning multiple responsibilities
like using market research data to formulate brand strategies, managing various stages of the brand life cycle, and performing other tasks such as juggling budgets and building a strong rapport with multiple stakeholders.

As someone interested in becoming a Brand Manager, you should first of all warm yourself up to the fact that strong data handling skills will be the backbone of your career and the key to success. Branding, marketing, sales, SCM – everything is data-based. It’s a highly valued, challenging, and rewarding career path to go down – and we wish you all the luck for it.

DATASETS THAT BRAND MANAGERS DEAL WITH – NIELSEN DATA

Nielsen is one of the most prominent names in data and market measurement. It measures media audiences such as TV, newspapers, radio, etc. Nielsen provides Data as a Service (DaaS) which includes access to 60,000 consumer segments, globally, and 300 media & marketing platforms.

Here are some of the common columns present in Nielsen data:

Market
This Column comprises all the individual and combined market i.e. States, Zones, All India, etc.

Geo Classification
This column contains classifications such as Metro, Zones, States, and All India

Brand
Brand includes one’s own brands as well as competitor brand names. Total rows include the Brand, the Category in which the brand operates, and the company to which the brand belongs

Sales Value & Sales Volume
Value comprises the Market Sales Value, while Volume means the Market Sales Volume in Kg

PDO Val Rs.
PDO stands for Per Dealer Offtake. It is the ratio of sales per outlet/store, or volume, to the total number of dealers handling the product

PDO in Units
This is the same as Per Dealer Offtake with number of units replacing total value

No. of Dealers
This is another metric provided by Nielsen, letting you know the total number of dealers in the market, brand-wise

NumD & WtdD
Numeric Distribution is the percentage of stores where a brand is placed out of ‘n’ total stores. Weighted Distribution is the percentage of stores with a good potential for sales of a brand, out of ‘n’ total stores

SAH Val
Suppose you are present in an outlet. Now, what is your brand’s share within the sales of a particular category in a particular outlet? That share would be called Share Among Handlers. For example, the share of Cadbury within the total sales of chocolates that takes place in an outlet.

STR
Sell-Through Rate is the product inventory sold within a period. It is used to predict the demand for a particular product. One method can be studying the STR of similar products by other sellers. Avoiding spending on unnecessary product listings is another reason to study STR and improve cost efficiency

Stock Volume & Stock Units
These are the available Stock Volume at stores and the available Stock Units at stores

SEPARATE FILE FOR EACH, OR JUST 1 INTEGRATED DATASET?

We’re proposing the second!

Explorazor combines not just Nielsen, but also Kantar (if FMCG industry), IQVIA (Pharma), and your primary sales, secondary sales, and more, into 1 integrated dataset available to you on the Explorazor screen. From there,

  • Ask queries via simple search interface
  • Obtain data pivots as tables, in seconds
  • Choose to customize tables into charts, trend graphs, etc.
  • Choose to download as CSV and transfer to Excel
  • The option to pin a query result to the dashboard is also present

Not only this, Explorazor also directly recognizes time-based filters, has an intuitive search query mechanism, supports time-period comparison (such as Sept 2022 vs Sept 2021, or Nov vs April 2021), and allows drill-down and drill-across to facilitate root-cause analysis, through simple clicks.

Features so good, we had to embolden the entire paragraph.

Related: If you’ve reached here, we’re sure you’re very interested in becoming a Brand Manager. Why not get a glimpse of how Brand Managers work on Excel? Head over to Modeling Basic FMCG KPIs in Excel.

Continuing, we believe that the value of Explorazor is clear for all to see. Instead of working slowly on slow laptops (large files; slow processing), there’s the option to work fast on fast laptops. Users also avoid repetition; the integrated dataset produces the required data pivot in one go. With a cleaner laptop and fresher mental space, Brand Managers test out hypotheses at accelerated speeds, improving the quality of their decision-making.

Which is really the end goal of all this incessant data crunching, wouldn’t you agree?

Explorazor is a product of vPhrase Analytics.

Take an Interactive Product Tour of Explorazor

Product tour

4 Ways Explorazor Differs from Power BI

by adminin Brand Managers, data pivots, Explorazor, Power BI

In this blog, we are going to explore 4 ways Explorazor differs from Power BI. Power BI is a data visualization tool that allows users to build interactive dashboards and BI reports. Explorazor is a data exploration and analysis tool that helps Brand Managers obtain data pivots instantly, through simple querying on an integrated dataset that combines Kantar data, IQVIA, Nielsen, primary sales, secondary sales, and more.

The common base between Power BI and Explorazor is that they both intend to help users make better sense of their data, and subsequently improve the quality of decision-making. 

How they do this is very different, and this is what we are going to explore:

4 Ways Explorazor Differs From Power BI

  • Made for Everyone 

One of the primary ways Explorazor differs from Power BI is that Explorazor is build for everyone from Business Users, Business Analysts to Data Analysts. Where Power BI helps Business Intelligence professionals and Data Analysts across industries, the ease of Explorazor, of searching using keywords makes it easier for every persona to perform analysis and take action real time.

Everything in the Explorazor UX/UI is upfront, neat, and conveniently placed. The left panel contains the Dimensions and Measures, the search box is at the top, and the answer covers most of the screen in the center. 

There are customization options available to convert tables into charts and graphs, but Explorazor is focused more on ease of usage and simplified presentation easier to perform ad-hoc analysis in real time and helps them obtain instant data pivots, rather than the more intricate, perhaps complex, dashboard and report building customization options provided in Power BI.

  • Smartness 

In no way are we suggesting that Power BI isn’t smart. Far from it. Users using Explorazor find that it is smarter ‘in context’. Let’s see an example:

Business User from the Marketing Team need to see the monthly/quarterly trends of a metric, say Market Share Value.

Explorazor supports this search query:

Likewise, as you will see in the next point, Explorazor not only supports time-based queries, but does that in an intuitive fashion. Because we have built the tool specially for everyone who wants to analyze data on fly, we understand the power of efficiently furnishing these basic results.

Explorazor’s has a simple purpose, and it’s a powerful one: whatever basics Users need, furnish them instantly.

  • Intuitive 

Explorazor lets you achieve a single result through multiple, natural ways. Look at this image as an example:

Whether you type q2 22, q2 – 2022 or quarter2 2022, you can expect a response to be produced. Explorazor basically understands the intent of your questioning. 

Another example:

Users are also able to compare custom time periods, like 

  • Sept 2022 vs Sept 2021, or 
  • November vs April

On a related note, search functionality is straightforward too: If you have multiple KPIs and cannot exactly determine your search query, just start typing and the system will prompt suggestions. 

Another method is to scroll through the left panel and double-click on the metric to add it to the search query.

  • Deep Exploration 

If there are certain parameters in Power BI which you want to look at but which are not present on the dashboard, you cannot do so until you edit the entire dashboard. 

With Explorazor, users can drill down into as well as drill across a particular data point. Root cause analysis is performed below on the Market Sales Value. We choose to drill further by ‘location’ and are immediately able to identify that Kansas and Texas seem to be areas of bother.

Moreover, one can go from a brand to a sub-brand to an SKU on Explorazor – through simple clicks. 

To Conclude

Explorazor is not here to compete with Power BI. It simply seeks to engage Business Users and Data Analysts in comparing the utility of both tools in their daily activities. Explorazor is designed specifically for Brand Managers – so why not explore it? 

Take an Interactive Product Tour of Explorazor!

Product tour

Why Should an Insights Team Consider Explorazor for Brand Managers?

by adminin ad-hoc query, Brand Managers, dashboarding tool, data pivots, Excel, Explorazor, Insights Team

In this blog, we’ll be making a case for why an Insights team should consider Explorazor for Brand Managers, discussing the problem with current dashboarding tools, and how Explorazor will benefit Insights Teams massively. 

Before we begin, just a quick introduction to Explorazor – it is a data exploration tool designed specifically for Brand Managers to obtain instant data pivots on an all-inclusive, integrated dataset, using a simple search functionality, with the ability to pin insights to dashboard and download any data point as a CSV file.

Let’s begin:

Introduction

Now, a part of the job for an Insights team is to introduce new products/tools in the company to help Brand Managers –

  1. Extract the maximum out of the data – as in, extracting the best insights which lead to the best decisions
  2. Doing so in a manner that eases, not complicates, a Brand Manager’s interactions with the data 

We interviewed 100+ Brand Managers from Unilever, Nestle, Reckitt, Glenmark, Godrej, and more, asking them about the lives of Brand Managers and the various data-related challenges they face. We then developed Explorazor, the data exploration tool in question, in such a way as to 

  1. Help Brand Managers get any data pivots instantly
  2. Ensure that it is so simple, that Brand Managers have no difficulty in adopting it

Regarding the instant data pivots, it is possible on Explorazor because Explorazor hosts all data in an integrated manner. Think of Kantar, Nielsen, IQVIA, primary sales, secondary sales, media, and every other dataset, all combined into one. Regarding the instant adoption, there is no end-user difficulty in usage, nor is there any novel proposal – Explorazor simply seeks to improve their Excel experience, without leaving Excel entirely.

Brand Managers are strikingly similar in their possession of skill sets, job roles, and the right personality traits, so the background they came from didn’t prove to be an adoption hindrance as well. 

The Problem with Dashboarding Tools

The major part of a Brand Manager’s job is to ensure that the brand is operating smoothly, across geographies. To do this on a typical BI dashboard, they would have to make, manage, and maintain tens of dashboards at a time. Workload is increased. 

Additionally, the data is stored individually, with no communication between them whatsoever. Creating a connection between them to answer ad-hoc queries is a painstaking task, and Brand Managers simply ask the Insights Team to revert with an answer to their ad-hoc queries. 

Finally, even if the dashboarding tool is able to do all of this, Brand Managers educating themselves on the ins and outs of the tool and how to use it, is, simply put, not going to happen. As a Growth Analytics Lead of a 35,000+ employee company told us “There are so many tools in a company, but nobody uses them. They just pose questions to us!”

Such is the case of the average company – BI tools that help create dashboards are lying unused because they don’t help people (in our case, Brand Managers) ease their daily lives. 

Benefiting Both Parties

The primary reason for Insights Teams to consider Explorazor for their Brand Managers is that Explorazor empowers the Brand Manager to ‘Do It Himself’. No longer is the Brand Manager dependent on anyone to run ad-hoc analysis. The win-win here is that the Insights Team’s time is freed up to concentrate on what they should actually be doing – strategizing for the long-term, running different types of modeling on different datasets to create better forecasts and targets for the business, and so on.

Consider an example: Suppose your company owns an apparel brand present in retail stores across the nation. Now as an Insights Team, you can focus on things like mapping out the loyalty base in each region, and studying why it is shifting, if that’s the case. You can then start benchmarking competition and finding out if a particular campaign they ran during that time period led to a shift in the loyalty base. If sales showed de-growth in stores in a particular city during the year-end, you can dig deep to find the exact answer for it – it may be something as minute as the discount scheme offered by competition being better than yours. You can design loyalty programs to win back your customer base, in addition to ensuring you have a better discount scheme the next time around. In a utopian and very possible scenario, Brand Managers would be thanking you over emails and town halls. 

All of this is possible, if only you have the freedom to execute what you are capable of.

Insights team should consider Explorazor for Brand Managers. If you are interested in knowing more about Explorazor, kindly schedule a 30-min demo call with us here.

If you want to understand how Explorazor helps Brand Managers explore data on an integrated dataset, we suggest you skim through the ‘3 Types of Analysis Brand Managers can Perform Super-Easily on Explorazor’ blog. 

Take an Interactive Product tour of Explorazor.

pRODUCT TOUR

3 Types of Data Analysis Brand Managers can Perform Super-Easily on Explorazor

by adminin Brand Managers, data analysis, Data Exploration, Excel, Explorazor, querying

Explorazor is a data exploration tool designed specifically to help brand managers in their day-to-day data analysis and exploration, which they’d otherwise do on Excel.

The Explorazor platform provides Brand Managers with a single view of all their data. With data analysis made easy and fast through this single-view dataset, Brand Managers are also able to accelerate the speed of their hypothesis testing. All they have to do is use a simple search interface to get the answers they are looking for, in the form of relevant pivots/charts.

Explorazor - Making data analysis easy for Brand Managers!

Here are the 3 Types of Data Analysis Brand Managers can Perform Super-Easily on Explorazor:

  1. Category vs Your Brand 

Let’s say you, as a Brand Manager, need to look at your brand’s performance in relation to the performance of your brand category. This is helpful in tracking the market, detecting consumer trends, and comparing how relatively strong a market is, with its overall sales. 

Let’s look at an example of how Explorazor makes it easy and quick to search your data and get answers instantly.

Above is how a search query and the result look on Explorazor. You can see the keyword-based query conducted which, if translated to an interrogative sentence, reads as ‘What is the Market Sales Value of our brand Alpha Supplement and how has it performed with respect to its Category, on a quarterly basis?’ 

  1. Competition vs Your Brand 

The next type of data analysis is Competition vs Your Brand. Once you’ve identified your competitors, consistently measuring their performance helps you benchmark your own growth vs. theirs. 

Further to querying, Explorazor allows you to pin your answers to the project dashboard, which means that all pinned answers are updated every time the data refreshes. The need to re-query the same thing is eliminated.

Let’s look at the ‘Competition vs Your Brand’ query here. As you can see, there are more inputs in this search query than in the last one. The query reads as ‘Comparing the average Market Sales Value, Net Spends on TV, average Share amongst Handlers of our brand Alpha Supplement as against other brands, for the last quarter.’

Using the customization options above, one can also convert the table into a chart of their choice. 

One can easily pin the query using the available icon on the top right, and add the particular query to the dashboard.

  1. Compare Primary Sales, Secondary Sales and Market Sales

To compare and analyze primary, secondary, and market sales values in Excel requires separate access to 3 different datasets. The results have to be then collated to get a complete understanding. 

Since all datasets are connected in Explorazor, you can simply access the single integrated dataset and obtain answers swiftly, with a single query.

Here we are comparing the average Market Share Value, Net Spends on TV, average Share amongst Handlers of our brand Alpha Supplement as against competitor brands, for the last quarter.

The default tabular format provides a clean and familiar look for Brand Managers to analyze the data, and is downloadable as a CSV file too, in case it needs to be transported to Excel for further exploration.

Directly Proportional – Quality & Speed 

The quality of decision-making is directly proportional to the speed and convenience of the hypotheses testing process. Systematically investigating the validity and reliability of multiple areas of interest simultaneously serves as a solid foundation for incremental improvements that may have otherwise not been possible. De-cluttering a Brand Manager’s mind space by providing an integrated data view and freeing up their time through data cuts at their fingertips will work wonders for both the brand and the manager – and that is what Explorazor is all about. 

Take an interactive Product tour of Explorazor.

Product tour

3 Data-Related Challenges Brand Managers Face and How to Solve Them

by adminin Brand Manager, data analysis, data cuts, Data Exploration, data-related challenge, Excel, Explorazor, pivot

Tell us a better love story than Brand Managers and data.

Brand Managers possess some of the strongest number-crunching skills in the industry. Everything’s solved and managed in Excel; sales, logistics, marketing; development, execution, evaluation. Operations and decisions are dependent purely on data, and these invite data-related challenges as well.

Let’s look at 3 data-related challenges Brand Managers face, and the possible solution to each:

Data-Related Challenge 1 – Data Fragmentation

The swiftness of strategic decisions suffers the most when data is fragmented across files and sheets. The data currently residing in Excel is stored under different column headers and cannot be combined. Internal and external data reside separately, and pivots have to be repetitively extracted from each individual dataset to move further with the analysis.

Fragmented, unsynchronized datasets also affect the quality of insights derived. One reason we can think of is the sheer (and avoidable, as you will see in the solution) manual effort BMs put in, in bringing the data at one place to perform analysis on it.

Solution

We have a tailored method to organize your data. Explorazor by vPhrase Analytics is a data exploration platform built specifically for Brand Managers to query their data better and extract instant data cuts from it. What Explorazor does is combine all the datasets currently residing in Excel, and provide unified, single-view access for Brand Managers to explore. Examples of such datasets would be primary sales, secondary sales, Kantar, IQVIA, and more. 

Explorazor relieves Brand Managers from having to constantly switch between files and sheets to find relevant data cuts. Correlating reasons for market loss, estimating the right media budget spend, gauging discounting effectiveness, finding best-performing regions, etc. become much easier. We imagine that a seamless experience will encourage Brand Managers to explore further and deeper into event root causes, key focus areas, and other ad-hoc analyses.

Data-Related Challenge 2 – Data Standardization

Metric definition is the first hurdle in the data standardization process. What Nielsen defines as an Urban area and a Rural area and what internal company definitions for the same terms are, are mostly dissimilar. Information capturing done by field sales personnel contains numerous kinds of errors. The spellings are different, the name of a state is mentioned in a shorter form, capitalization issues, etc etc. 

Raw data standardization is a necessary prerequisite for efficient data analysis, and right now it is a task that Brand Managers would love to sweep off their table.

Solution

Our team at Explorazor ensures that all your data is modeled and standardized so data analysis can be conducted without having to worry about missing data points.

Redundant, duplicate, inaccurate, and irrelevant data is expelled, leaving a de-cluttered dataset that serves as a base for higher-quality analysis and insights extraction.

A clean dataset is also helpful when creating routine dashboards and presentations for senior management.     

Data-Related Challenge 3 – Large (and Clumsy) Data Dumps

The data dumps that Brand Managers work on are too large – Excel cannot output results fast on our laptops, as one would like. Loading – and ensuring that the data is saved – takes excessive time. An abundance of formula insertion slows the workbook down. 

Thinking about quick pivots? Think again. Then again, and then again, because your laptop is slow and you have lots of time on your hands…

Solution

Loading huge Excel files is no joke. To create pivots, and to create them now, is one of the prime reasons we believe a solution like Explorazor will go a long way in assisting Brand Managers save time. All data resides on servers and is accessible via a browser, so laptops breathe freely again. Brand Managers, using a simple search interface on Explorazor, can conduct ad-hoc analysis and test out hypotheses at accelerated speeds. 

If you want to take the pivots to Excel – permission granted. All pivots are downloadable as CSV files. Convert pivots into charts using simple customization options and pin them to pinboards. Each project within Explorazor allows its separate pinboard creation.

Explorazor is built for Brand Managers

Explorazor alleviates data-related challenges which Brand Managers face, as well as: 

  • Saves their time by taking the processing load off their laptops
  • Eases their data exploration journey by providing unified access to all their datasets
  • Enhances the quality of their insights by standardizing all current and incoming data
  • Increases their independence by letting them conduct ad-hoc analyses on their own, without over-reliance on BI/Insights teams 

Take an Interactive Product Tour.

Product tour

Modeling Basic FMCG KPIs in Excel

by adminin Brand Managers, Data Exploration, Excel, Explorazor, FMCG

This blog will introduce you to how Brand Managers model basic FMCG KPIs in Excel.

There are a lot of articles that touch upon the life of a Brand Manager and the various responsibilities they shoulder. Here we will put a microscope on just one of the numerous calculations that Brand Managers undertake, and learn how they find business improvement areas through data analysis.

If you are a Brand Manager, we recommend you skip to the end of this blog to ‘Basic FMCG Modeling Made Easy’ or read ‘Complementing Excel – How Brand Managers can Simplify Data Exploration and Analysis’.

Let us understand how to obtain Gross Margin, Net Margin, and Operational Profit. Arriving at these numbers helps Brand Managers analyze where they are losing their margin – is it at the production level, is it the cost of sales and marketing, or is it the head office costs? Brand Managers thus have a sense of direction to initiate further data exploration and make optimal, data-driven decisions.

Let’s begin:

Part 1 – Obtaining Net Margin

  1. Unit Gross Margin 

Unit Gross Margin Depends on two things – 

  1. The average price we are getting from the middlemen, or if we are directly selling to the customers, from them 
  2. Subtracting the unit production cost from this average price 

So Unit Gross Margin = Avg product price (say Rs. 70) minus its production cost (say Rs. 40) = Rs. 30

Note: The unit production cost is again dependent on two things – 

a. The total fixed cost divided by the total quantity produced, plus 

b. The unit variable cost

There are further sub-calculations in each component. For example, Total Fixed Cost (FC) includes salaries to be paid, which is typically generated as: taking the number of full-time employees or full-time equivalents (FTE), setting an average salary per FTE, and assuming some social securities as a percentage of the salary. The salary excludes the bonus earned by the employee.

  1. Gross Margin 

Once we have the unit gross margin and the total number of products sold, we get the Gross Margin easily enough.

Gross Margin = Unit Gross Margin x Total Products Sold

The Gross Margin will be calculated for various channels we are selling through, and a year-on-year, or month-on-month record will be maintained too.

As you can see, such calculations require Brand Managers to be detail-oriented, organized, knowledgeable and possess a deft hand at Excel.  

  1. Sales and Marketing Costs 

Obtaining the Gross Margin has covered the Production Cost. We have yet to factor in the sales and marketing costs, so let’s do that. Sales and marketing costs depend on the size of a brand’s market share. A bigger market share means we are selling more, which means that the costs attached to sales and marketing per unit is lesser. 

Marketing elements would include –

  • Social Media
  • TV ads (computed as the number of campaigns multiplied by the cost of 1 campaign)
  • Outdoor campaigns
  • Loyalty programs
  • Market research
  • Mailing

Components of cost of sales would be –

  • Salaries
  • External services (cars, phones, fuel, etc)
  • Materials & Energy
  • Other related services

These would be calculated for both retail chains where we supply directly as well as for the traditional stores that we reach via wholesalers.

  1. Net Margin

Part 2 – Obtaining Operational Profit

Deducting Head Office costs from the Net Margin gives us the Operational Profit. Head Office costs include –

  • Salaries
  • Material and Utilities
  • Maintenance
  • Rent (for offices and warehouses)
  • Depreciation and amortization of assets

Part 3 – Zooming Out

Converting all numbers into percentages for easier visual view, the final output would be like this:

Basic FMCG Modeling Made Easy

The above KPI modeling and profit calculation require a Brand Manager to continuously switch between multiple tabs and insert various formulae to get the figures. The same process can be augmented through Explorazor, our data exploration tool. 

Explorazor combines and hosts all datasets, for example, market research, internal sales, Nielsen data, etc. in an integrated manner. Brand Managers thus obtain a single view of the entire dataset. From there, they can extract data cuts instantly through a simple search function of using column names as keywords.  

Explorazor also allows 

  • Visualizing pivots as charts
  • Pinning the charts to a pinboard, and 
  • Downloading them as CSV files

Moreover, all data resides on servers and is accessible via a browser. Laptops are thus relieved from the burden of processing huge datasets. Brand Managers are further liberated when their reliance on BI teams is reduced. The acceleration of ad-hoc exploration is experienced immediately with Explorazor.

Explorazor is built for large enterprises, with single sign-on, row and column level security, data encryption, and on-cloud and on-premise availability.

Do you want to see other features added to Explorazor? Write to us at sales@vphrase.com. If you want to see the product in action, take an interactive Product Tour.

pRODUCT TOUR