What is marketing analytics?

Marketing analytics provide us with all the data we need to gain insights into customer behaviours, competitors, and industry trends to help inform our marketing activities. When used optimally, analytical methods can help us discover new markets, untapped audiences, and areas rich with development opportunities. Some brands and companies have analytical data spanning years – they’ve tracked customer behaviour from their purchases through to their social media interaction with the brand. This bank of data can be drawn upon to measure all kinds of activity and answer key marketing questions.

The ways that data can be read and used are infinite, but here are a range of different analytical techniques favoured by marketers.

Marketing mix modeling (MMM)

This is an advanced analytical technique that uses big data which has accrued over years but which may be difficult to assess or analyse because there’s so much of it. Deciding what needs to be measured – the variables – and why, is the first step. In fact, MMM is considered by some to be a data science so to really take analysis to the next level, marketers may want to work with data scientists.

MMM is particularly concerned with four different factors, sometimes referred to as the Four Ps:

• Product: The unique selling points and benefits of the product or service itself. 

• Price: The price point at which the product is offered, plus discounts or promotions.

• Promotion: The methods by which the product was promoted such as email newsletters or social media campaigns.

• Place: The channels in which the product is marketed and sold (e.g. online, in stores, by mail).   

The choice of variables in MMM tends to be pulled from these four groups. For example, marketers may try to determine if more sales resulted from a product being advertised via a banner ad or via a targeted email campaign. The volume of sales is often used as the dependent variable, while the independent variables represent certain elements of the marketing process. A statistical technique known as multiple linear regression is then used to find a relationship between the dependent variable and two more or independent variables selected from the Four Ps. 

Unmet needs analytics

The name tells us the purpose of these analytics: identifying the unmet needs of customers. Unmet needs analytics can be gleaned from product reviews, surveys, focus groups, and customer service feedback. Google Trends is also a great free tool to see what people are specifically searching for in relation to your product or service. In terms of surveys, there’s no need to write huge questionnaires – Instagram allows you to create quick surveys and posing questions on Facebook can give you instant insights into what customers want. If you do have more than a few questions to ask or want to get an in-depth understanding of a customer segment, Survey Monkey is an easy to use interface both for marketers and the survey recipients.

Brand analytics

In this category, qualitative data is as important as quantitative data because it’s about how people feel about your brand. Often, sales teams and customer services teams will have knowledge regarding this subject. As they’re at the frontline of any business they may have insights into opinions that customers aren’t always willing to share or that the business is not actively asking them about. A key example of this is the Thoughtful Marketing Movement started by Bloom & Wild. The letterbox flower delivery company listened to feedback from customers that Mother’s Day email campaigns triggered sadness for them if they had lost their mother or were not close to her. They created an opt-out for marketing around this celebration and later went on to do the same for Father’s Day and Valentine’s Day. Many other brands joined the movement, and this seemingly small adjustment has changed the generalised approach to marketing emails. This improves long-term brand reputation even if it’s not a strategy that directly drives sales initially.

Pricing analytics

Pricing analytics help you find out exactly how much your customers would pay for your product. It’s especially useful in highly competitive markets where it feels like everything that can be done to optimise sales has been done. Pricing analytics uses data mining as well as forecasting models and algorithms. It also often involves multiple business experiments that can be run in parallel quickly and easily so you can measure what is likely to happen with each price change.

In a report by Deloitte, it was noted that pricing analytics can increase profit margins by 2 to 7 percent in just 12 months, with an ROI above 200 percent. It’s a metric that’s important to look at on a regular basis to ensure you’re getting the most from profit margins. For example, when attracting new customers with discounts, it’s vital to ensure that long standing customers also receive regular rewards or promotions. When customers are paying full price they should also feel that it’s good value and good quality or you may lose them after initial sign-up.

Market size analytics

This is a method that should really be applied before a business starts to understand the growth potential in what you’re proposing to sell. But if your business expands or pivots and branches out into other areas, you will need to understand this potentially new market and its customers. The size of a market can be measured by:

• Volume (how many units sold)
• Value (money spent in that market)
• Frequency (how often a product or service is sold)

Looking at competitors in that field will give a fuller picture of whether it’s a promising area in which to expand.

Competitor analytics

Identifying who your real competitors are helps you identify who you really are as a business. Who do you consider as in the same league as your business? Which businesses do you aspire to be in the same league as? Many businesses find themselves too busy to carry out data analysis on competitors, but it can be invaluable. The challenge is that it’s most useful to have insider information on their operations while still acting ethically. Observing competitors’ activities can offer routes into drawing their customers to you if you feel that they’re missing a vital point which you can then leverage in your communications. Business journals, annual reports, and product brochures can all provide information that can help you see the chinks in your competitors’ armour. 

Non-customer analytics could also be grouped within this area of analytic data. Understanding why a customer chooses a competitor over your business can be extremely illuminating. It may simply be because they’re unaware of your product or service and its benefits, which can help you improve your marketing material and reach. Social media can be an ideal way to connect with non-customers.

Demand forecasting

This marketing analytics technique aims to predict future demand for a product or service, based on historical sales data or market analysis. Time series analysis is often used, which looks to past sales to recognise cycles and trends that are likely to reoccur.

In uncertain times, demand forecasting is important for all parts of the business – particularly for logistics and supply chains – but demand forecasting also has a direct impact on marketing activities. With more accurate forecasts that take in multiple factors, you can determine the best time to launch a new product or when to offer sales or discounts in periods that are traditionally slow.

Trend forecasting

The landscape for trends forecasting is very fast-moving, especially since a lot of businesses have moved primarily to online sales since the Covid 19 breakout. Predicting the next trend for consumers is not as consistent as it used to be – or as safe a bet – even if you have data from previous years. Supernova is a self-proclaimed iconic lifestyle brands company – they hold multiple brands under the umbrella of Supernova. All their brands are created from rapid testing and surveying on social media before and while launching. Everything from the name to packaging and campaigns are moulded by real-time insights and customer demand or preference. Viral marketing and influencer-generated content is part of their marketing mix and they have found a successful formula that works for them.

At the core of their business are trends – social media trends and skincare and beauty trends. It’s a savvy combination that anyone can apply to their own business, since social media is such a key ingredient to marketing success. It’s true that the boldest companies can create trends, but conversely, spotting a stagnant trend can be a real opportunity to disrupt. Ultimately, the key to trend forecasting is knowing your sector and business inside out rather than jumping on a trend which may be over by the time your product or service reaches market.

Take a strategic approach to your marketing career

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