Reports suggest that in the next three years, the share of marketing budget that is spent on analytics is expected to more than double. Marketing tactics such as targeting ads by demographic are no longer adequate for keeping customers happy (and loyal).
Improving the brand loyalty of existing customers is often more profitable than on-boarding new customers, with a five per cent improvement in customer retention potentially resulting in a 95 per cent profit increase. With so much data out there, there is no reason to continue relying on gender, age-group, or location to predict what a consumer might be interested in. Of course, age and location help when tailoring communications, but they are far from being most indicative of consumer behaviour.
Pushed along by consumers’ increasing expectation for personalised communications and offers, businesses often find themselves making the mistake of falling back on social listening technology. Social listening will enable brands to use social media to gain insights into the interests of your target market and monitoring brand performance across social platforms. However, it’s easy to make the mistake of thinking that social listening is enough to shape your marketing strategy; while it does deliver holistic insights about your consumer base, such as how often people talk about your brand or what time of day your customers are most active, it doesn’t deliver the much needed insights into each customer at an individual level.
Because of this, social listening platforms only enable you to tailor your marketing and communication based on the behaviour of whole groups of people. This means that, rather than delivering a bespoke and relevant service to each individual, you are delivering something that you think they probably want based on the average behaviour of the group they are placed in.
Retailers and other consumer-focused businesses end up falling in the trap of marketing to huge groups of people based on presumptions about that group. However, a new trend has seen consent-based analytics tools empower consumers to get the communication and offers that they actually want. Instead of constantly seeing ads or receiving emails for something irrelevant just because that’s what people in their age-group tend to buy, what they receive will be constantly relevant – designed specifically for them.
Big data analytics tools can help marketers truly understand consumers on a more personal level. Knowing what consumers desire in a product; what they want in a brand; what services are relevant to them; and even what puts them off, can completely revolutionise the entire marketing strategy of a business.
The amount of data out there is significant but a consumer’s digital footprint is ever growing. What is difficult for marketers is leveraging this data to create usable and actionable insights, particularly considering that a significant proportion of online data consists of qualitative data; how can you know what an individual is talking about when they mention ‘working’? The word could indicate being employed, or it could easily be ‘working hard at the gym’, ‘working hard on my dissertation’, or ‘working on the car’. For this reason, the tool you choose needs to have an element of text analytics, such as psycholinguistics and natural language processing, in order to derive accurate meaning and avoid simple errors like assuming anyone who mentions ‘work’ is employed.
As well as this, it is vital to ensure that the tools you use deliver real-time insights so that what your offering is constantly adapting alongside their changing needs. Targeting a customer based on their wants and needs from six months ago could result in the offering being irrelevant and could cost you their loyalty.
For example: Mark signs up for an online account with a shoe retailer. He likes long distance running and often tracks his runs and posts the results on Facebook as motivation. Additionally, he has recently been talking about his upcoming participation in The London Marathon. The shoe retailer can then use this knowledge to market products for training (such as shoes to break in), products for the actual event (such as blister plasters), and products for after completing the marathon (such as a foam roller for sore muscles or heat packs for injuries). By using the right analytics technique, this retailer can adapt what they offer based on Mark’s changing needs as well as predicting what he may be interested in in the future in order to remain constantly relevant.
Utilising data insights to engage with consumers effectively allows brands to develop and maintain unique one-to-one relationships. Fundamentally, by using these tools, brands can get as close to a real relationship with their customers as possible without physically meeting and talking with them.
The more you learn about your customers, the more you can personalise communications and offers which has the power to turn both retention and acquisition marketing on its head.
With 16 years’ experience in the data and software industry, and a background in credit risk and fraud prevention, having worked at leading companies such as Call Credit, James Blake oversees all operations within Hello Soda, an advanced big data analytics company. He passionately believes that modern businesses are empowered by innovations in data technology, ensuring that Hello Soda develops only the best software solutions.