Big data is being touted as the answer to every marketer’s dreams, but what makes it different to the data they have always had access to? Perhaps the key elements here are volume and currency, the latter in terms of being recently acquired, even in real-time.
Almost all retail or customer facing enterprises have been collecting and storing key data for years. The type of data, the volumes and length of time they were kept was determined by the cost of storage and processing. As those two computing elements have dropped in price we have seen an explosive growth in not only the volumes but also the ‘depth’ of data being kept.
Early marketers saw the value in analyzing customer buying habits, sales hikes after promotions, determining the most popular product lines and the times people were most likely to buy new items. This was done using historical data, usually by querying key record types in their databases, or extracting that data, normalizing it and then processing it via a data warehouse.
This avoided placing excess load on the ‘live’ systems but the data used was only a subset of what could have been extracted and used if computing costs allowed. The concept of ‘currency’ of data was only dreamt about and not thought to be of great value because campaigns and promotions took months to put together and launch.
Fast-forward to low cost, virtualized data servers that store and process data at volumes never before imagined. Intro the concept of ‘big data’ best described as the exponential growth and availability of data, both structured and unstructured. More data leads to more accurate analyses, and that allows marketers to focus their attention not just on broad demographic groupings of customers but right down to an individual level.
Customer data is no longer limited to what is being recorded on internal systems, but unstructured data can be sourced from social media and online services such as Google and Amazon. This volume of data creates new issues including how to determine relevance within large data volumes and how to use analytics to create value from the relevant data.
The velocity of which data is being presented poses the next challenge, and being able to react quickly in determining what data is of value, what should be utilized immediately and what to do with rest is key to its successful utilization.
The third ‘V’ word used to define big data is variety, and it is the merging of structured data from traditional databases with unstructured data from text documents, email, video, audio, messaging, social media and financial transactions that is both challenging, yet incredibly rewarding.
Armed with this new arsenal of information marketers are now able to identify the key buying traits of an individual customer, combine it with their current online activity and make recommendations tailored exclusively for that customer – all in real-time.
They are now able to focus campaigns to a personal level, making the customer feel more important and increase the chances of success. Traditional marketing costs though media channels is inherently expensive but being able to target prospects via their online devices is far better directed, more personal and much more cost effective.
The success or failure of these personal campaigns is analyzed so that any future efforts take them into account. As SAP states in its own marketing materials: “More accurate analyses may lead to more confident decision making. And better decisions can mean greater operational efficiencies, cost reductions and reduced risk.”
Does this confirm that big data is the answer to every marketer’s dreams? Maybe not just yet, but it certainly will help them sleep a lot better.