Creating solutions, strategy and media planning are a must know for marketers in today’s world. However, lately there is another skill set that is a pre-requisite for all marketers, of Big Data, Consumer Insights and Analytics. These 3 terms are really creating a buzz and contrary to the popular belief that you need technical knowledge for complete data understanding, it can be pretty ‘easy peasy lemon squeezy’ if you put a bit of logic to it.
Big data has been in the picture now for 5 years which started with giants like Google and Facebook storing consumer data. It was when they started storing data for the brands who advertised on their platform that data analysis and consumer insights came into the picture. In this competitive and every changing advertising landscape only giving brands a platform to advertise wasn’t enough. Answering the why and why not’s of campaign performance, what works what doesn’t and then creating actionable insights to better campaign ROI became a must. Soon, all stakeholders, be it publishers, networks and agencies were creating tools to predict and optimize campaigns with end-to-end service of data collections, data analysis and consumer insights that help yield better campaign results.
Now, every brand wants a data-driven strategy, be it creative or media related to creating a fool-proof campaign which has a higher probability to succeed when compared to a campaign that is not driven by data. Though, the question that still lurks in the mind of data scientist is that do marketers actually know about these three pillars of data driven strategy? Do they know that they need different skill sets? Do they know that they can’t be leveraged singularly, that these combined together create the best data driven strategy. Here we will talk about the difference between these three and talk about how to decode them individually and together.
Did you know that we have created more data in the last 2 years than we have in the entire human history and that we collect more than 1.7 MB of data every second?
The three pillars of data driven strategy:
Pillar one – Collect data
Pillar two – Apply analysis to the data
Pillar three – Interpreting insights from the data analyzed
What is Data?
Everything starts with collecting data. As soon as a consumer registers to your app, subscribers your blog, view your ad or even login to their email account, the data collection process is already in que. Demographics data, geographic data, psychographic data and their purchase cycle, all is data and this data superimposing more data in called Big Data.
What data tools?
The first step to data is raw data collection. Microsoft, SalesForce, Oracle and Adobe are few initial names that started collecting data on website traffic and transactions. The collection of data has now become more industry specific. Brands still use these software heavy companies to create big data sets for them, integrating them with several other tools they use to get numbers from various media components they use for their marketing initiatives. BARC for TV, Hootsuite for Social, Litmus for Email Marketing, Apsalar for app attribution, Google Analytics for website analytics, KISSmetrics for e-commerce analytics and finally, brands also use marketing automation tools like Marketo for centralizing their entire marketing role with data, analytics and marketing engagement. (There are several more good tools under each marketing component available, you ca pick and choose as per your organization’s marketing requirement)
Which skill set?
You need technology knowledge for creating these tools when you are the one writing the algorithm for this. People with a background in IT, Computer Science (SAS, SPSS, R, Python etc.) and Mathematics are the one who write and crack the permutations and combinations of data collection.
The next step of data collection is Analytics. It is a trend or a pattern that comes out of your data. Without analysis data is of no use, it helps in uncovering the tremendous opportunity that data brings. It’s after analysis of the data when you can work towards an insight.
With the above mentioned data tool, data is stored. However, the analysis bit comes from strategists in the business. Technology guys lay the foundation for data collection, then the structure is created by the analytics team. Analytics team pivots data shared with them and create several data possibilities to get to know how they influence each other. For instance, how does time of the day affects online sales or how the change in UI design affects App traffic.
What Skill set?
Strategists are people with marketing, economics, business and statistics background. People well worse with analysis theories. However, experience matters more than these educational qualifications. A person working in the industry for 3 to 4 years would know about the work more hence can analyze it better with our without the above said backgrounds. They can be content and research professionals; they can be strategists and account/client managers.
Insight is a value that is created from the analyzed data. Insight is what helps in making business goals and decisions. Till the analysis isn’t converted into an insight, a step to mold the business into the right direction or solution to a problem is not possible. Insights professionals are the ones who collect the data and findings of the first 2 steps and create something that will make sense to a layman. Mostly many brand heads and decision makers (other than marketing heads) don’t understand what is analyzed until put on a slide by insights team that helps them understand the final steps to be taken for the betterment of their business in simple language. Collating publisher data, reading post evaluation and past campaign performance is another part of insights.
In today’s scenario very few agencies have insights professionals, generally data and analytics team are created and insights are left for brand side to take care of. Very few marketers on the brand side have knowledge of data and analytics, let alone creating insights from them. Insights professionals are the roof of the architecture of data and analysis. They give closure to the entire process and put the final full-stop of business decisions made.
What skills are needed?
An insight professional can be anyone in the system for a year plus. A person from either planning, content, research, marketing or strategy background who is a little curious on data mapping and is eager in working with all sections of a business to create the best insights.
Example of Data, analysis and insights working together:
Example of data: In Diwali an e-commerce app saw 30% low sales in women’s ethnic wear compared to the same time last year. On the other end the men’s ethnic wear sales grew over 100%.
Examples of analysis: Comparing the above scenario with last year we saw that women ethnic wear had 15% more off than this year. This resulted in 30% more sale last year compared to this year. Moreover, the men’s ethnic wear had no discount and this year has a discount of 15% resulting in the hike in sales in the current year.
Examples of Insight: The insight was to increase the discount on the women ethnic wear by 10%, so that the sale increases and matches what was reached the previous year. There is no need to make any changes in the discounts in the men’s ethnic wear section.
How they help each other together?
It was after marrying these three together is when we received a palpable answer that will stabilize the situation and work towards a growing business. A lack of insight can result in lack of consumer retention. Churning data effectively empowers the marketers to engage with their audience in an optimum manner, proactively creating better business opportunities for themselves in return. The process has to be completed for business to reap on the money they invest on them.
On the skills note, even the skill set is overlapping. You can be from ay department or with any educational background to be in data aggregation, analysis or insights creation. You have courses online that you can study to create a product and be in tech even if you have an arts background. You need not be a strategist to be an analysis professional and for insights you don’t need to be an MBA. If you are in the business for 2 to 3 years you are educated enough to be a-part of any department. The only thing needed is to be up to date as new technologies and new learning are frequently added.