Big data, is it a buzzword or a useful way to talk a new scale of data analysis? Each website we visit, each location we Map, these are data points which when taken in aggregate become useful in pattern of life analysis. If you analyse enough patterns you can build archetypes. Archetypes are simplified versions of people are part of a feedback loop in marketing, psychology and life in general.
Building complex profiles based on inordinate numbers of variables is used in marketing to help businesses reach who they think will make them money. 58% of Chief Marketing Officers say big data is most useful in SEO. If we unpack the implication of this search engine optimisation is the pursuit of trends key words and topics. These can be tied to seasonal events, such as Christmas or public holidays. Or they could be the consequence of viral content spreading through the network. Epidemiology, counter-terrorism, surveillance, marketing. These diverse fields are united around the methodology of Big Data because of its prediction powers.
#1 Better predictions
Previously predictions you could be certain of were linked to traditions. As state previously, holidays provide regularity. The meaning of holidays can shift over time but the ossification of a specific weekend in July or a Monday in August gave marketers a specific timeline for buying and selling certain things. With Big Data we’re being given access to more traditions and patterns of life previously hidden. Or at least not celebrated with fireworks. The danger here is that we get carried away with ourselves, algorhythms aren’t built with psychological health in mind, only profit.
#2 Small Business Big Tools
Access to big data analysis is increasing. Thanks to software as a service and the ability to work with marketing teams anywhere in the world costs are low. The biggest challenge is to start. Identifying the critical pieces of customer information relevant to a particular business is the the first step. Converting marketing into a form of surveillance is getting easier. Sending multiple forms of advert or custom offer simlutaneously (to separate clients) produces data points on a variety of factors that can be pulled apart by analysis.
Big data is one of the building blocks in building algorithms. Without ample data algorhythms are unable to learn. Big data orbits on the scale limit of human understanding. We need artificial intelligence to reduce elements and conduct tasks to big and complex for us. Automating processes increases efficiency, but we have to be mindful of keeping humans in the loop.
#4 Custom-er pricing
Big data has been shown to help marketers and businesses make better pricing decisions. This is “$9.99 vs $10.00” strategy on steriods. Consultancy firm McKinsey found on average 1% increase in price equates to 8.7% increase in operating profits. Making minute adjustments to prices, based on complex understandings of networks and behavioural economics, gets results.Each invoice, email, engagement on Twitter will contain multiple pieces of data. Aggregation of these can reveal patterns of life in businesses which can be turned into strategy for interactions.
#5 Customers loyalty
Using Big Data to improve customer loyalty is great rhetoric. Analysing who customers are is part of the co-optation process of business. This is best achieved through total dominance of a customers technology, companies out there want to get as much data as they possibly can out of you, before it becomes ‘instrusive’. The ubiquity of all this data is that companies can begin to brand themselves. Once a sufficiently utilitarian facet or a major niche emerges in the consumer base the company itself will be able to transform into exactly what the customer wants it to be, a reflection of their best self.
#6 Virtual campaigns
When I swap music recommendations with my friends there is a persistent percentage which they have already heard. For the simple reason that YouTube recommended it to them. Just as it recommended to me. The analysis used to decree a level of certainty I will like a song can be replicated on any topic.
Big data has many applications. Ultimately the methodology is designed to appraise the probability of something occurring. That something is whether you’re interested in being a customer.