But analytics is a broad term and can include or exclude data from every part of the customer journey. It’s not just about websites either – organic search, social media and paid search are all rich sources of information and need to be tracked to ensure you’re getting the full value from your marketing.
Are you reaping the data benefits from all these sources – or just some?
Social retargeting is a powerful tool to drive down ecommerce cart abandonment rates and recapture existing customers, who are 14 times more likely to convert that first-time customers. But it’s potential to target prospects at a very granular level and to then see how different campaigns progress provides a mine of data for marketers to use.
Running A/B tests on a similar group of customers or potential customers gives quick data on which type of offer is more compelling, the different preferences of various audience segments and how compelling different landing pages are.
This can be linked with other forms of social media data, whether it is channel insights, brand mentions or listening, to build up a detailed picture of who your customers and followers are and when they engage and buy. When this is funnelled back into your digital marketing strategy you can refine social media, landing pages and content to provide your customers with just what they want – and what makes them buy.
Lead generation tracking
The preference for using analytics over a single channel of marketing data shows how important it is for marketers to track their user’s journey, especially as it’s quite common for people to use multiple channels and devices before converting. For example, customers might initially find a company through paid search, revisit on an organic search for a brand name and then switch devices to buy.
For repeat customers, this might be more complicated as social media, especially Facebook, is driving more sales than ever before. So if you’re using analytics to drive your marketing strategy, it’s important that it gives you as close to 360 ̊ view as possible.
BPP, a leading specialist education provider were using PPC to drive inbound leads but as most of their conversions happened over the phone they were receiving at least 1,000 calls a month that they couldn't attribute to a lead generation source. This made it difficult to focus their attention on the keywords and onsite resources that drove calls.
After integrating call tracking with their PPC campaign they could easily see which keywords generated offline leads and optimise their campaign accordingly. In a month this resulted in over 15% more calls and year-on-year call volumes increased by 30% as their campaign became more targeted and efficient.
Both these forms of analytics look back at the journey of an existing user, whereas predictive analytics uses existing data lakes, combined with machine learning and statistical models to discern what customers are likely to talk about, or buy, next.
As a turbocharged form of social listening, it allows content and social media marketers to be proactive rather than reactive, creating updates and content that positions them as trend spotters or thought leaders within their niches. Using this requires a degree of flexibility in strategy, though, and discernment on applying mined data to your particular audience.
Predicting which customers are likely to buy which product next or who is more likely to become a lifetime customer brings a whole new level to personalisation and segmentation. Resources can be laser targeted at more valuable customers across multiple channels, prompting them to take the next steps that will turn them into a long-term customer.