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Data Analytics Is Disrupting These 4 Martech Roles – Which Role Suits You Best?

Predictive analytics in marketing technology, (martech) is passé!  And while over the years data analytics has become the baseline skill for marketers across industry verticals, analytics is still driving big change. This change is not just limited to staffing in a marketing department, but also in attracting data-savvy professionals who can combine financial, marketing and analytical skills.
According to a recent Gartner CMO spend report, CMOs now allocate 27% of their budget towards technology. The increased spend highlights the use of leading-edge technology in providing top-notch customer experience and fine-tuning marketing performance, not to forget to outclass the competition.
Data analytics has become the standard practice across domains and we believe it is time to look at new analytics functions that will drive forward-thinking organizations that want to make it big in digital. As the McKinley Marketing Partners report sums up, digital marketing is on the rise, but the marketing professionals of the future must be both experienced marketers and critical thinkers, with the ability to analyze data. With marketing on the path to automation, Analytics India Magazine and UpGrad narrow down a bunch of emergent data analytics job functions in martech.

The martech landscape revolves around these clusters:

  • Advertising

  • Content

  • Social & Behavioral

  • Commerce & Sales

  • Data Management

Data Analytics Is Disrupting These 4 Martech Roles - Which Role Suits You Best? UpGrad Blog

The future of marketing is shaped by new roles in data analytics. Here are the skills that are most in-demand:

1) Algorithmic-led marketing:

With search becoming predictive, what with Facebook, Twitter and Google giving tailored recommendations, brands need more behavioral data powered by Artificial Intelligence (AI) to better understand the customer decision journey, drive engagement and cross-sell products. Another area where AI and machine learning comes into play is in dynamic pricing. Case in point – cab aggregating apps Ola and Uber’s surge-pricing algorithm (wherein prices peak when the demand is high). Through dynamic pricing, brands can see substantial gains in profit margins.

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Data savvy marketing mavens must already be familiar with Programmatic advertising, hailed as the future of advertising wherein cutting-edge machine learning algorithms are used to automate targeted ads for customers. Case in point is Programmatic advertising for media buying that enables the brand to customize a message for the right audience via audience insights from the brand for search, display and social media.  Over the years, programmatic advertising has moved into the mainstream with data-driven advertising companies using it for informing TV and radio advertisement spends as well. The advantages are manifold – optimize KPIs in real time and utilizing data from multiple platforms as users move from screen to screen.
Who’s fit for the job role: Data Scientist, Data Analyst & Machine Learning Engineer
Skills Required: Researching and understanding user behavior patterns such as customer engagement, building machine learning model prototypes in R/Python for in-depth analysis. Broadly speaking, one needs to have a solid foundation in CS and statistics, math, modelling and analytics.
Proficiency in:

  • probability and statistics
  • ML algorithms and libraries
  • computer science fundamentals & programming
  • data modeling & evaluation are necessary

Average Pay Package: 12- 18 lakhs per annum
Relevant Companies: Amazon India, Google, Flipkart, Adobe, InMobi, Mu Sigma, start-ups such as Crayon Data and Bridgei2i

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2) Mining the Social Buzz:

Customer listening or social listening as it is popularly known is the #1 priority in organizations across the board. From monitoring brand engagement across digital touch-points to customer engagement, the job entails driving personalized real-time actions across channels.
The demand for social media analytics is emphasized by a research report by McKinley Marketing Partners that cites that digital marketing expertise is the most desired skill of 2016. According to McKinley’s research, around 90 percent of marketing roles need analytics or digital marketing experience. Industries, agencies and leading brands have deployed social listening tools to better track and monitor brand health.
Who’s fit for the job role: Social Media Listening and Brand Analyst, Social Listening and Digital Insights Manager
Skills Required: Job entails analyzing data, based on customer/brand sentiment, product experience, customer relations management and preparing comprehensive reports. The job also involves mining data from social channels and turning into reports that inform inventory decisions. Familiarity with text mining techniques and natural language processing is needed. Industry experience across domains such as BFSI, FMCG and telecom and knowledge of data visualization tools is a must.

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Proficiency in:

  • making reports using data analytics tool
  • preparing reports using web analytics
  • working with high volume and multi-platform data
  • branding and marketing experience is necessary

Average Pay Package:  INR 570,000 onwards
Relevant Companies: Nestle, GroupM
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3) Managing Data Management Platform:

DMP is akin to a data warehouse, a platform for storing and analyzing campaign and audience data. It provides one point access to marketers to source and manage data such as cookies and identifiers for data segmentation. The information is used for creating focused campaigns based on segmentation. Some of the big players in the market are Adobe AudienceManager and Oracle DMP.
Who’s fit for the job role: DMP Consultant
Skills Required: It’s a job that spans all industry verticals, hence a deep vertical industry experience is a plus. Knowledge of digital marketing and Google analytics suite is a plus. This is a customer-facing role that requires identifying new business opportunities. Knowledge of the internet and online advertising, including using data for targeting and measurement is a must have.
Proficiency in:

  • making reports using data analytics tool
  • conversant in DMP technology
  • HTML, Java, SQL
  • strong sales acumen
  • online technologies are necessary

Average Pay Package: INR 1,24,000 per month
Relevant Companies: Adobe, Oracle, Accenture

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4) Market Research Analysis:

To succeed in the age of data-led economy, organizations need to understand what their consumers want. This is where market research analysis comes into play. Analysts study market conditions, consumer behavior and monitor competitor activity by analyzing a vast amount of data through statistics, predictive analytics and data-driven tools.
The findings of market analysts have a significant impact on an organization’s products or services. Data-driven marketing plays a huge role in skills thoroughly grounded in data analytics, CRM, customer experience modeling and a solid proficiency in data management systems.
Who’s fit for the job role: Marketing Analyst, Market Research Analyst
Skills Required: It’s a job that requires working in collaboration with data scientists, statisticians and converting research findings into graphs via data visualization tools.
Proficiency in:

  • big intelligence tools such as Tableau
  • information science and statistics
  • visual analytics
  • knowledge of the web and direct marketing are necessary

Average Pay Package: INR 826422 onwards
Relevant Companies: Deloitte, Accenture, E&Y, HP

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What are MarTech Roles?

Marketing technology, abbreviated as MarTech, refers to the combination of software and technologies that aid in achieving marketing goals and objectives. It has become a standard element of digital marketing initiatives and also be used to improve marketing efforts across all channels. Two conceptual axes in Brinker's paradigm lead to four sorts of MarTech roles: maestro, marketer, modeler, and creator. The four separate responsibilities are divided into two categories: external (audience outreach) and internal (marketing activity coordination). They're also measured along a spectrum that includes both technology (creating and utilizing it) and process (how it's done) (strategy and execution).

What is Social Media Analytics?

The capability to acquire and make sense of the data gathered from social channels to support business choices and assess the success of actions based on those decisions through social media is known as social media analytics. Likes, followers, retweets, previews, clicks, and impressions obtained from specific channels are not included in social media statistics. It also differs from information provided by marketing campaign support providers like LinkedIn or Google Analytics. Social media analytics is carried out using specially built software platforms that function similarly to web search engines. Search queries or web 'crawlers' that cross channels are used to retrieve data about keywords or subjects.

How does DMP help Businesses?

A DMP can help professionals and businesses from many industries across the world. A data management platform (or DMP) unites the process of collection, organization, and activation of first, second, and third-party audience data from any source, including online, offline, mobile, and beyond. It's the foundation of data-driven marketing, allowing companies to acquire unique insights into their customers. It also collects and organizes data from a range of different data sources and delivers it to other platforms such as DSPs, SSPs, and ad exchanges for targeted advertising, personalization, content modification, and other purposes.

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