Utilising big data for marketing is a practise best suited to B2C. It’s an assumption that many B2B organisations are struggling to shake off, and recent reports are finding that many B2B marketers are still failing to find ways to use it effectively, if at all.
True, fears about the validity, quality and disparate nature of their data are legitimate reasons why they may be reluctant to put big data to use. However, there are data cleansing, enhancing and processes to unify a customer database to address these issues respectively.Data governance issues aside, leveraging big data into a marketing strategy can have a significant impact on customer relationships and customer support, as well how leads are nurtured leads and marketing can be personalised.
As obvious as it might sound, one of the priorities for marketers is to establish who their ideal customer is. Using existing customer data as a starting point, marketers can employ insight tools that look at their organisation’s market penetration, then assess common patterns relating to their customers’ revenue, growth potential, cost to serve, and so on. This identifies a company’s most valuable customers and provides a ‘dream customer’ profile to apply to the wider market in order to find others who also fit that profile. This data insight can also be used to identify promising new target markets, as well as those ripe for cross- or up-sell of services, driving revenue and helping with the acquisition of new and more profitable customers.
With lead scoring and lead generation strategies established, big data is used to monitor the progression of prospects and customers through the sales funnel. At the top end, this involves tracking the activities of web visitors to establish their status as a lead, and any possible intent to purchase. For example, this could be the process of filling out forms, downloading white papers and case studies, registering for webinars as part of the research stage of their journey.
Each of these actions generate data that not only help identify potential leads (to learn whether they conform to their criteria established for ideal customers) but whether their behaviour means they should be passed onto sales straight away, or require further nurturing by marketing to a point where they would appreciate speaking to a salesperson.
Big data can also be used to tailor the delivery of online experiences, depending on a customer or prospect’s stage in their journey. Marketing analytics tools can segment customers within a database to target with a relevant email marketing campaign, for example, while personalisation tactics can help push them towards content that will encourage them further down the funnel. This could mean recommending a returning visitor to an appropriate white paper, or creating a personalised homepage for existing customers that highlights other services they might require.Improving the customer experience is a key aim, but deeper knowledge of your customers through the use of big data also means you can minimise the cost to serve, while also building loyalty and improving engagement, which will help with retention, too.
Of course, tackling the aforementioned data quality issues will remain a stumbling block for those without no data hygiene routine or a 360-view of their customers. But a continued reluctance to put big data to use could see you losing the customers you love, even missing perfect prospects entirely.