The fairy tale of Big Data-Driven Marketing

Bringing insights from data ‘behind the scenes’ to improve business outcomes

In the present day, Big Data and Analytics is being used to improve operational efficiency, understand customers better, get real-time insights and provide a personalised user experience, thereby leading to greater customer satisfaction.

The chart below shows the results of a survey, conducted to understand the impact and value of investing in Big Data, by Fortune 1000 companies. A majority of respondents (49.2%) affirmed that big data initiatives brought tangible results in revenue growth.

You can’t manage what you can’t measure - Peter Drucker

We can see that big-data is the ‘big’ thing today, in a context of brands and their growth. But how exactly can these massive stores of data about consumers be used effectively?

The answer is: Data-driven marketing.

Juxtaposing data with creativity

Let us look at a specific example of the strategy used by a leading new-age company, Spotify (a music streaming service with over 75 million users and 25 million subscribers), to understand how they use data insights creatively:

Spotify’s major competition comprises of Pandora, Apple Music, Google Play Music and Amazon Music, all backed by their mothership companies. Compared to the scale of these aforementioned companies and their massive marketing budgets (barring Pandora), Spotify smartly distinguishes itself with its data-backed innovative marketing strategies.

Their Golden Marketing strategy: A powerful narration created by capitalising on insights gathered from big data.

It is the ability to deliver the more relevant, personalized and contextual experiences for our users at the intersection of data, technology and storytelling - Mayur Gupta, Spotify’s global VP for growth and marketing

In the month of November 2016, people in the U.S., U.K., France and Germany saw Spotify at its playful best: an ad campaign highlighting some of its users’ quirky habits, gained from insights of their data over 2016.

This OOH (Out of Home advertising) campaign was both a strategic and branding success. Spotify followed this success by extending the strategy to other platforms (summarised below):

1.The OOH campaign generated buzz with catchy key-phrases like- ‘Thanks 2016, It’s Been Weird’ and quirky user habits.

2. Users as the brand ambassadors : an e-mail campaign ‘Your 2016 on Spotify’ having personalised music statistics, getting people to talk to each other, leading to word-of-mouth publicity.

3. Celebrity driven buzz: Spotify released a commercial in Feb 2017, featuring lead singer of dance-rock band DNCE: Joe Jonas, reacting to how a Spotify user listed the band’s song on a playlist titled “Play This at My Funeral”, where Joe wonders how it would be like. 

Within four months, the video went viral, garnering over 4 million views, transforming into a meme, flooding Twitter and Youtube comments.

Data has been, and will be, a big part of our storytelling. Rather than make up a story, we find it interesting to see data about actual people, and then tell it in a narrative that’s interesting. It’s a big part of our differentiation - Seth Farbman, CMO Spotify

So, what can we learn from Spotify? How can the power of Big-Data and its analytics be incorporated into marketing strategy?

 I have delineated the strategy behind Data-driven marketing, as per my understanding. Outlined below is the broad process of incorporating data analytics into marketing, which I would term as the D5III signifier:

1. Defining the business objective
2. Decide the measurement priorities
3. Data Collection
4. Data Cleaning and processing
5. Data Analysis

The 5Ds, followed by;

6. Innovative Interpretation of Insights (III)

Breaking this down, we can understand each of these steps as:

Defining the business objective

 Begin with a clearly defined problem — ‘What need gap are you going to solve? What is the objective of planned activities? The objectives should be SMART (Specific, Measurable, Attainable, Relevant, Time-bound).

Decide the measurement priorities

It’s important to set up measurement processes before collecting data, which would ease the process of validating the analysis in later stages. Certain priorities that matter in this context could be timeframes, units, frequencies etc.

Data Collection 

Data can be collected from multiple structured/unstructured sources. It’s important to know what data will be required that caters the objective(from the above point), what are the existing data sources within the organisation that can be utilised for the same and what third party data providers to be sought out for obtaining the rest of the information. Additionally, it is also necessary to determine the storage system to be used and naming convention to be followed that keeps the team in sync.

Data Cleaning and processing 

After raw data collection, there has to be a process of sanitising through these databases, finding overlaps, redundancies, irrelevant fields etc. This is a critical step, necessary to avoid states of confusion and prevent recursive comebacks for the analyst for clarity.

Data analysis 

This phase incorporates checking whether the results validate the initial hypothesis, understand if there are any other angles that were not considered initially and see whether the results are aligned with the objective. This is an ‘advanced’ state of processing data where they are organised into understandable, legible and usable data-sets.

Innovative Interpretation of Insights (III)

The final, most crucial step. Yes, we have a well organised set, showing relations, anomalies and new discoveries. The insights gleaned from having a well-curated dataset are then to be carefully interpreted for actual real world implications and uses. This is where the marketing wizards need to play the role, like in the case of Spotify where it was used to create an interesting conversation with its users, thus ‘humanising’ the product and making it more ‘friendly’ and ‘ relatable’. Different business domains could lead to different innovation, but the need is to constantly ideate and innovate for a better use of this powerful tool present for us.

We live in interesting times, an era where the ‘use of data’ carries more meaning than just having it. This digital era offers unlimited opportunities, bound only by imagination. 

So, How are you using your data? I would like to hear some interesting insights.