The amount of data that businesses have available today is growing fast. It’s expected to increase ten-fold by 2025, offering an unparalleled opportunity for organisations that take advantage of it. Now, there are a wealth of new data sources coming to the market thanks to smart home devices and the Internet of Things. Savvy marketing teams have already taken full advantage of this. 92% recently surveyed are investing in marketing analytics over the next year, and the marketing analytics market is growing by 14.3% year-on-year. But with so much data at our fingertips, organisations don’t just have to use it – they also have to gain tangible business value from it.
A heap of analytics
This is something easier said than done; the explosion of data has brought with it a plethora of different analytics tools. Every day seems to bring a new innovation to the market. For the C-suite, being able to sift through these choices effectively is paramount. Especially in marketing, where the number of analytics tools is particularly high (and expanding at a rate of 14.3% every year).
New tools allow marketing teams to optimise across the full marketing mix. There are recommendation engines, sentiment analysis, better solutions for targeting and also determining attribution. Marketers are on the cusp of a revolution – they can now achieve things with data that they could only have dreamt of a few decades ago.
Link back to your goals
But you can’t let yourself get carried away by the hype surrounding advanced analytics; any new analytics capability must always link back to your core business objectives. It needs to feed back into and complement your marketing strategy (and wider business goals). In doing so, you ensure any innovation you do implement will have a benefit that your marketing team and the entire organisation can see.
Make it part of every day
The second step to gaining value from any analytics function is to make sure it’s part-and-parcel of daily operations.
This involves change management as much as it does strategy. In order to make change stick across your organisation, it’s important to ensure buy-in at all levels. Leadership, in particular, needs to visibly support any analytics project.
Develop a data-driven culture, whereby employees switch from gut-instinct decision making, to data-first. To achieve this, people must experience the benefits of analytics in their daily work – which could be as simple as providing insights on a new landing page, to more advanced marketing attribution.
Everything you do must also tie back to your business and departmental goals. You can’t prove the value of analytics if the results don’t move the organisation towards reaching its goals.
Whatever analytics solution you implement, it must be user-friendly. People won’t use a tool if it adds effort to their work day (no surprise there!). Ongoing user feedback and engaging employees with testing new tools is a good way to achieve this.
Advanced analytics for marketing
As previously mentioned, there are a load of analytics tools available for nearly every marketing problem. Of these, the most likely to unlock value include:
Customer acquisition: Data can provide marketers with behavioural, socioeconomic and demographic insights to improve targeted and acquisition. Forecasting tools can predict how effective a campaign can be, which in turn informs budget and KPIs. The Weather Channel has been using climate data to predict the buying behaviour of consumers. It offers this to advertisers to create hyper-targeted ads. For example, a sunglasses brand could target customers in hot regions and a moisturiser brand could target people in dry conditions.
Customer retention: Retaining your existing customers involves providing them with a superior service and always adding value. One good way to achieve this is through more personalised suggestions provided through a recommendation engine. This has the added benefit of upselling. Amazon is a common example of this in action, but Netflix and Spotify also use data for this function. Analytics can also be used to determine churn and develop strategies to attract lost customers back.
Coty has just launched its personalised beauty offering: Let’s Get Ready. The skill on the Amazon Echo Show, is informed by data on a consumer’s hair, eye, and skin colour. It provides recommendations on looks, make-up tips and Coty’s beauty products. Users can add Coty’s products directly to their Amazon basket. It also syncs with Facebook to proactively suggest looks and products for upcoming events.
Promotions and pricing: 30% of pricing decisions made by companies fail to reach the best price. By using data, you can determine the best price point for each customer based on whether they have purchased from you before, their price elasticity and likelihood to purchase. This can be used for new product pricing as well as determining how much to reduce a product line by. Combined with data on manufacturing costs, this strategy can help an organisation determine the best price to maximise profits and sales.
Customer service: Tying into customer retention, by using analytics to measure the effectiveness of your customer service you can identify any issues early-on. Sentiment analysis and social media monitoring can help. Call centre data can be analysed to determine whether customers have had a positive, neutral or negative experience. Social media data can flag any negative mentions of your company, or alternatively, positive experiences that should be amplified.
PR: Measuring the effectiveness of PR campaigns has always been a little tricky because of differing success metrics and the inability to fully link sales to coverage. However, data is making this a possibility. Social media data can show whether engagement spiked after a particular news story, for example. It can also warn you of an impending crisis that might impact your organisation.
Social media: There’s a wealth of insight available through social media data. Social listening can inform product development, how people view your brand, and warn of any risks to reputation. Social connection analysis maps out the connections between different groups of people. This allows you to identify new potential target audiences. For B2B marketers, it can identify other related companies that you should be targeting. It also informs how you communicate to them, including your tone of voice and method.
Samsung uses social listening to determine the success of product launches. It also tweaks marketing campaigns based on its own social media data and competitors’ data. When competitor Huawei launched a phone, it heavily pushed its slow-motion capability. Because of this, Samsung then altered its campaign to focus on the same function in its latest handset.
There is huge potential for using analytics in marketing, and it’s set to grow. The key for all CMOs now is to narrow down the range of choices into ones that deliver value to your organisation – and quickly. The second step is to gain widespread buy-in for your plans. Without everyone on board, your analytics projects will be stifled. There’s a lot that you can do with data. Start with a few small projects to prove the value, and then progress onto something more ambitious.