The report contains input from CRM strategist and consultant, Andrew Campbell, and Dr Duncan R Shaw, an information systems lecturer based at Nottingham University Business School.
Below, our two independent experts provide answers to some big data questions.
What does ‘big data’ mean?
“I think of big data as the minute-to-minute personal diary of everyone and everything; the detailed description of everything that we do and everything that our machines do on a very granular level.
“So instead of starting with the data that we have and looking for things that we can do with it we should start with what business needs and then work backwards to find the data that will enable such services, insights and analyses. Don’t get wrapped up in the data, the new analytical toys or the technology – just think about what you need answered right now.
“‘Big data’ is also the label we’ll use until we have some idea of what novel opportunities and services will emerge from this complicated mix of sensing, processing, analytical and visualisation technologies. Although it is fragmenting and specialising already so there may not be a single label like ‘Web 2.0’.”
Dr Duncan R Shaw, Lecturer in Information Systems at Nottingham University Business School.
“Data becomes a valuable corporate asset when it is translated (by data analytics) into actionable insights that allow a brand to create value for a consumer by understanding their needs and delivering to these. Initially the core data set related to significant customer events: customer enquiries, purchases, survey responses and service interactions.
“The internet and digital communications introduced a whole new set of micro-customer events (web site visits, search patterns and content down loads). Mobile and social channels create even smaller scale, nano-customer events: like; share; comment; check-in; tweet; content creation/upload.”
“The increasing volume and granularity of these customer events mean that the data is ‘big’. It is also often user-generated, unstructured and text-based making it complex. These factors make life hard enough for marketers looking to meaningfully interpret the data. However, even bigger complications lie in the contextual (customer, internal and external circumstances), temporal and geographical dimensions that have to be understood and applied to data analysis in order for valuable and actionable insights to be drawn from it.”
Andrew Campbell, CRM Strategist and Consultant, and author of Econsultancy’s Customer Relationship Management in the Social Age Best Practice Guide.
What are the trends driving interest in this area?
“Different parts of companies are interested in different things. COIs see this as a way to sell internal changes such as de-fragmenting data silos. Marketers know that using mobile devices as the glue to hold together an omni-channel strategy requires big data capabilities. Smart people in all business functions have been itching to measure the performance of their part of the business in more detail and to try out their creative ‘what-ifs’ more easily.
“Another driver is creating an indispensable customer experience. Bribes like card points are not the true drivers of loyalty. But Usefulness, Ease and Enjoyment create an indispensible service. All three need a very deep and real-time understanding of each and every customer throughout the whole relationship journey.
Dr Duncan R Shaw
“The search for an enhanced and differentiated consumer value proposition are the key business drivers. Brands that can engage consumers in an on-going dialogue across all channels and use the interactions to create a deeper understanding of current and future consumer needs and behaviours will be better placed to deliver to these needs – and thereby drive sales.
“The new data sets represent a new raw material that marketers can refine into insights that can help them optimise the marketing mix to deliver competitive advantage over brands that do not have this decision support capability.”
What does big data mean for businesses?
“Big data + cloud = big company services for small companies.
“All the staff of firms in a supply chain are like retail consumers – so all the consumer analytics and retail service uses of big data have parallels in B2B.
“Larger than human-scale analytics is needed to produce smaller than human-scale services which can orchestrate second-by-second experiences for individual consumers, i.e. vastly detailed descriptions of populations of customer journeys and huge collaborations of staff networks are required to increase the granularity of service experience.”
Dr Duncan R Shaw
“Big data provides a vehicle for ‘big insights’ to enable brands to understand and deliver to consumer needs. The big winners from big data will be those brands that can industrialise and operationalise this process and wire it into their:
- Strategic planning process to spot and key exploit opportunities/mitigate threats and create the optimal organisational culture and structure.
- Marketing processes to engineer and design a stronger (and more profitable) consumer value proposition.
- Front office processes to deliver an enhanced consumer experience (and incremental sales).
- Back office processes to reduce costs and increase operational efficiencies.”
Why is big data particularly relevant for marketers?
“The relevance for marketers is the bridge between the creative and the nerd. Sandboxing means that creatives get to cheaply test bigger ideas as fast as they come. The data nerds get to measure everything then optimise it. So creatives and data nerds finally see that they are doing similar things, just with different haircuts. Marketing is turning into a science.”
Dr Duncan R Shaw
“Big data embodies the very essence of marketing i.e. understanding customers’ current and future needs. Customer relationship management strategies were built on a single customer view of the customer. From this came basic segmentation and customer lifecycle management based on behavioural analysis.
“Web analytics provided deeper insights and greater scope for personalisation and timely, relevant customer interactions. Mining the social and mobile data sets has increased the breadth and depth of personalisation but the ultimate goal is still the same.”
What could and should organisations be doing now to harness big data?
“First: use data to understand the personal context of their consumers’ journeys at every single stage – every touch point is a two-way street. Use this understanding to be indispensable to their consumers by helping each stage to be easier and more fruitful. Even B2B firms have consumers – the staff of their customers.
“Develop systematic analytical strategies: start with the same old fundamental business objectives and work backwards. Take a systematic view and think about outcomes and whole customer experiences. Don’t be confused by all the new toys.
“Data sharing and reuse: am I really sweating my data assets? Consider your data sharing policy. Do you exchange data with suppliers? For benefits in return or just to make them better suppliers. Don’t forget customer privacy and data protection.
“Data additives: what extra data do you need for actionable insights? The totality of the required data is rarely within a single firm.”
Dr Duncan R Shaw
“Big data is not precise science and there is no dot-to-dot approach. However, there are broad best practices which will serve brands well:
- Make customer insight a corporate priority with executive level ownership and accountability.
- Develop a formal customer insight strategy. Big data should be an extension of this rather than a new, discrete undertaking
- Put marketers at the heart of this process. They must identify the insights that will be most important in creating value for customers
- Complement them with expert data analysts and technologists that understand the available data sets and how best to mine them.
- Systematically link your customer insight strategy upwards into your broader business and brand, and marketing strategies downwards into your CRM programmes.
- Develop data quality management as a key IT/analytics discipline so that you can build on strong foundations.
- Create a robust data analytics environment and technology set so that analysts are productive and responsive.
- Adopt a phased, incremental approach to creating and deploying big data insights
- Test (often), measure (obsessively) and learn (quickly)
- Be creative and lateral in your thinking. Make sure this is all about marketing and customers NOT data and technology.”
What are the main challenges faced by organisations seeking to translate big data into action?
“Dealing with Fragmentation – multiple data sources, data stores, retail channels, mobile devices, business process silos, brand partners and other variables makes it very hard to make the business cases and design appropriate strategies, never mind action them.
“Sponsorship fragmentation: I’ve noticed that the issues and opportunities that surround big data cut across many types of middle manager so the sponsor has to be very high up. But this means that you have to sell big data on the high level central benefits even if these benefits are made up of many diverse benefits nearer the consumer or suppliers. Big data is about the very small as well as the very big – and every level in between.”
Dr Duncan R Shaw
“There are technical challenges relating to the scale, variability and complexity of the data sets involved. There are practical challenges relating to the type of human resources required to perform the analysis.
“There are commercial challenges relating to funding the investment in people and infrastructure required to ‘do big data’. However the biggest challenges relate to understanding the human, social, psychological and anthropological factors influencing consumer behaviour and locking these down into a solid theoretical and strategic framework.
“This is new territory for consumers and marketers and there are big issues around: privacy/permissions; ownership of data; (real and perceived) value of data (to the brand and consumer); consumers’ trust in and relationship with brands; social buying behaviours and appropriate level of personalisation.
“These will take time to form and settle and the most practical approach in the mean time is to experiment and use bottom-up, tactical initiatives to help inform and accelerate the top down, strategic debate.”