Oct 26 2015 | by BALTEG SINGH
Big Data is an umbrella term that encapsulates the four ‘V’s - volume, velocity, variety and veracity, which are the dimensions in which Big Data is measured. Due to the vastness of data generated from a myriad of sources, particularly in this digital age we live in, a whole new marketing landscape has been constructed.
To name just a few; Analytics, consumer behaviour analysis, machine-learning and predictive analysis are all born out of data mining and manipulation. It is impossible to avoid Big Data as it persists in our daily lives.
Data without inference is likened to a desert with no-one around to see the oasis. It is through trained eyes, using repeatable methods that companies can survive the desert and ultimately prosper. Using statistical analysis and computational methods; patterns and behaviours can be extracted and accurate insights can be gained. There are challenges in order to efficiently and optimally use this huge data, storing and analysing them to support meaningful decision making. However, in doing so, you can achieve better results from these more accurate, data-driven decisions.
The ubiquitous nature of data in a marketer’s world is not a new phenomena, however with the advent of the internet and advancements in technology, data is now a much bigger beast.
Customer data can consist of the following (not exhaustive) list:
All of which are multiplied by second by second activity - amounting to a gargantuan quantity of data.
What does this mean for digital marketing?
Inferences, insights and the way they can influence decisions based upon their conclusions are the primary motivating factors for pursuing the summit of the Big Data mountain. Including big data analysis in an overall marketing strategy can greatly impact the following areas:
For effective use of big data in digital marketing, a knowledge of what data to collate is quite a challenge since the magnitude is very much off the scale. Hence, it is more appropriate to keep the aims and objectives in mind to set context to what data will be useful. The right analytical tools can also facilitate the decision making process. These tools can provide data cleaning, analysis and aggregation. All this will serve in reaching conclusions for the questions we ask.
Perhaps the most important challenge with big data is going from insight to impact. How will the gathered analysis drive strategy and marketing direction? This question can only be answered when there is an alignment between the results obtained and the marketing roadmap as one feeds into the other. Due to volume of data and the law of large numbers, more often than not, the analysis lays a good foundation to explore possible strategic pathways and actions for growth. For proactive action from the insights, the knowledge must be transferred to those who can implement it for a bigger impact.
Some strategies for gaining and utilising Big Data insights
Google Trends is a great way to utilise Big Data. The ratio between a search term to the total search volume of trending topics aids marketers to determine the popularity of topics from varying stratums of data be it global or local. It helps keep abreast of relevant subjects that may influence businesses to consider when targeting their customers.
2. Data-backed analysis
Greater accuracy in profiling customers through data-backed analysis can assist in gaining knowledge about them and targeting them more precisely. This has become very accessible with the vats of data available. They reveal the granularity of information and the interactions of users that demonstrate behaviours and preferences. This can be retrieved from click events, social media usage and frequency of web sites used etc.
3. Time relevant targeting
This will help to underpin successful campaigns, click-through rates and help customers get more involved with your brand. The advantage of having timely insights of customer activity and behaviour allows businesses to prepare information and generate ideas more succinctly. This leads to a clearer roadmap for greater engagement with users.
4. Predictive analytics
Use predictive analytics to provide foundational basis for generating future leads. By looking at historical data of successful leads and applying data mining, statistical modeling and machine learning, predictions can be made about how to gain future leads. Including this analysis in lead scoring can illuminate which methodologies and strategies should be given greater attention for fruitful outcomes.
Big Data is everywhere and it awaits you with great potential. The sheer scale of it can be overwhelming, like a vast ocean with nothing in sight besides the wet stuff but using a measured and goal-oriented approach, the gains and insights can massively improve your business strategy and create better relationships with your customers. The utility of analytical inferences can show trends, behaviour, validations of hypotheses and drive data-backed decisions. It informs best practice and should be included as a component in an overall marketing strategy. Suddenly, the ocean does not seem like a scary place.
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Big data: are you geared up?