On January 14, Director, Marketing Technology and Analytics for Procter & Gamble India, joined Simplilearn to talk about how to succeed in a career in analytic marketing. He spoke about the importance of analytics to present-day marketing and why data analytics is an essential skill for marketers.

Which Half?

Jai started with a famous quotation from the 19th-century American department store founder John Wanamaker:

“Half the money I spend on advertising is wasted; the trouble is, I don’t know which half.”

Jai pointed out that marketing today extends far beyond advertising, but the principle of seeking to understand what works and what doesn’t drives marketing analytics.

What is Marketing Analytics?

Jai related marketing analytics to the four Ps of marketing:

  • Product. What is the right product for the market as it exists today?  The data from sales will reveal what SKUs are selling well or poorly in each market.  That helps reveal what product characteristics impact sales.  Data from customer feedback such as online shopping reviews and consumer complaints can reveal customer satisfaction and dissatisfaction and their causes, helping refine the product and your customer service to better serve the customer’s needs and desires.
  • Price. As important a factor as price is in the success of a product, it needs to be studied carefully.  Looking at price as a variable, you need to look at how price levels affect sales and profitability to determine the product’s ideal price in a given market.
  • Place. What channels of sales and distribution are you using?  Which retailers sell your product?  What are the formats you sell your products in?  For example, do you have different SKUs for individual packages for grocery stores and for bulk packs for warehouse club stores?
  • Promotion. Promotion includes all aspects of communication to potential customers.  Online and offline advertising produce different data: consumer responses to online advertising can be directly measured in clicks on ads, time spent on landing pages, e-shopping actions like add to cart, and actual online sales.  Online advertising can also be personalized, and analytics drives how and where this is done.  Offline advertising response is harder to measure directly and requires inferences from other marketing analytics models and tools.

First Framework: Collect the Reds

Jai described a useful framework for driving action from analytics, which he called “Collect the Reds.”  It starts with creating different views of your business performance from different perspectives: you can take “slices” based on customers, consumer personas, geography, distributors, SKUs, and any other relevant variables that impact your business.  When you create a slice - for example, sales volume in City A by SKU - you create a matrix of business results.  If you color-code this matrix, you would typically assign green to combinations (Jai calls these pockets) that are doing well (high sales of a particular SKU in City A), yellow to pockets with marginal performance, and red to pockets that are underperforming.

As a whole, sales volume in City A might be performing well.  However, looking deeper into the individual volume-SKU results might reveal areas of concern that need focused attention and intervention.  This framework lets you quickly zero in on problem areas to fix them.

One key to this framework’s success is to generate enough different slices (matrices of pockets) to reveal previously hidden “reds” and mark them for repair.  Another key is to understand for each of the “reds” what the cost to fix it will be and what the fix will return in benefit.  Typically there will not be enough resources to address all of the “reds,” and it will be necessary to prioritize them for the most return on the resources available.

Second Framework: Jump to Insights

In the second framework, Jai likens marketing analytics results to a 1,000-page book.  If one has to leaf through it page by page to find the insights in it, the process becomes unworkable.  If, on the other hand, one can jump to the right page with the insight, the book becomes far more usable and useful.

In marketing analytics, reporting tools and dashboards that force users to change parameters and make different drop-down menu selections to generate view after view of the data are like the 1,000-page book.  The users must look at one “page,” see if it has the desired insight, and then change parameters and selections to generate the next page, on and on until they reach a valuable insight. That process creates a barrier to finding and acting on insights.

Jai recommends that you think in terms of calibration.  You can use your own past performance as a benchmark and look at how your business’s performance has changed over time, or you can compare your business performance to that of your peers and competitors.  In either case, you are calibrating your results against a benchmark, and you can more easily see whether your relative performance today is improving or declining.

Skills for a Successful Analytic Marketing Career

Jai described the components of a successful career as an analytical marketer:

  • Business understanding. Jai stresses the importance of understanding the business you are trying to grow, and not just its marketing aspects. He recommends shadowing the people in your organization to learn how they carry out their work and what insights from analytics they use.  Research has shown that the best analyst is seven times more productive than the analysts in the bottom rank. That means there is a high return to your career on investing in building your skills and business understanding.  Jai also points out that a broad understanding of your business means you can contribute as an analyst in other functional areas besides marketing, which further increases your value to the organization.
  • Data. Today, organizations generally don’t lack data - they often have the opposite problem of data overload, making it confusing to choose the right data to analyze for the insights they need. Understanding data and gaining data engineering skills will help you to pick out the right data to use, ensure it is of good quality, and turn it into insights in a form that your organization can use.
  • Tools. Exposure to a broad range of current analytics tools - not just the ones your organization currently uses - will help you help your organization choose the right ones for its needs and will let you be productive with whichever ones are available to you.
  • Technology: you need to be a proficient user of technology.  Gaining skills in areas like database management and coding can help you be effective with analytics tools and systems.

Jai pointed out that a recent survey of Chief Marketing Officers asked whether they believed they had the right people in their marketing analytics function.  Only two percent of CMOs said that they did!  That means that there are a lot of CMOs looking to hire new talent in marketing analytics to build out their teams.

Jai responded to many questions from the live webinar audience.  To see the entire event, including the Q&A, watch the video above.

For more Simplilearn career resources in digital marketing and data analytics, including articles and ebooks, see https://www.simplilearn.com/resources. And if you are ready to become a learning individual by gaining specific skills and certifications for your career, check out the courses and programs Simplilearn offers, including the Digital Marketing Specialist Master’s Program and the Data Analyst Master’s Program.

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