Marketing is a vibrant, fast-moving profession that’s always improving and becoming more interesting: technology has given it speed and allowed it to explore new dimensions. It’s also a little too obsessed by The Next Big Thing. While the forward-thinking nature of marketing is one of its best attributes, it can also be dangerous.
New trends and buzzwords are thrown around like confetti, and treated as one-size-fits-all solutions to the complicated, unique problems of complicated, unique customers. In the recent past, big data, social media, and more have been touted as the cure for all promotional ills, and all have fallen short in some way or another.
It’s because marketing doesn’t need buzzy trends to be successful: it needs results. It’s easy to get so caught up in the romantic notion that we’re there to form an emotional connection with the customer that we forget that there’s as much science to our profession as there is art.
Going back to basics and focusing on the essentials of modern digital marketing is likely to yield more success. Here are six key areas to focus on.
Data has the potential to be a brand’s most valuable asset – but the operative word there is ‘potential’. It has no intrinsic worth, which is what makes the industry-wide overemphasis on “big data” so damaging. That you can capture vast quantities of information about your customers is often taken to mean that you should.
But ultimately, your business needs the right data, not just any data. It’s imperative that you identify what you’re trying to accomplish and who your target audience is before you gather any information. From there, it’s essential to identify the data you need to identify and message to this audience. Transient or session data can be useful for identification and segmentation, but do you need to keep it? Data needs to be actionable and available when required, but often ends up in data lakes ‘just in case we need it’.
Effective data management is aimed at having data available in the right form when required for segmentation and personalisation.
It’s hard to overstate the importance of personalisation to contemporary digital marketing. According to a recent Accenture report, over 75% of customers are more likely to buy from a retailer that knows their name, their purchase history, and can make recommendations based on this purchase history.
But personalisation isn’t always easily accomplished. The best place to start is by knowing where your customers live – figuratively speaking, of course. An omnichannel approach to digital marketing seems a little redundant when most brands are yet to get multichannel right.
If a customer prefers not to receive marketing communications via email, then it’s up to you to pay attention. In fact this is your legal duty. If they prefer to be reached via text message, or phone call, then send them an SMS, or ring them up. The data you accumulate about them should reflect their preferences, and technology will make them easier to parse.
Segmentation and profiling
A further step towards personalization is segmenting and profiling your customers. A business that targets its marketing strategy at anyone, everyone, and their extended families is a business that isn’t really targeting at all. This is especially true if your organization has a diverse customer base.
Understanding this customer base requires forming the most detailed view of each demographic that comprises it. Grouping them and forming buyer personas according to factors such as age, purchase history, preferred communication channels, and others, can help you determine what, when, and how a customer will spend money with your brand.
Gathering insights from customer information used to require a finely-tuned analytical skillset – the kind typically held by data scientists. Modern technology makes this much simpler. Profile information, purchase patterns, and preferences can be gauged in a few moments using marketing automation software.
Propensity modeling can effectively let you know what a customer intends to purchase, and when they’ll purchase it. It knows that, if an individual wants to buy a large quantity of desktop computers, it will probably also need a large quantity of monitors, keyboards, and computer mice. These are obvious enough correlations, but the right model will be able to highlight opportunities for relevant upselling and cross selling – and factor in the customer’s preferred method and timing for each purchase.
Single Customer View (SCV)
The single customer view (SCV) has long been considered the holy grail of marketing. Unlike the holy grail, it’s quite attainable. The aim of unifying customer information across all relevant channels is ambitious, but well within reach.
Building an SCV database is a matter of bringing together disparate silos of data from across the business – from sales, IT, marketing, finance, and customer service, among others – unifying them, and making them available to any employee who might need them. It makes analyzing and understanding customers much easier – and therefore it also makes sending them personalized communications much easier.
When we know what customers are doing, how they like to do it, and where they’re doing it, our job as marketers is at once simpler and more sophisticated. Focus on getting these areas right and make sure your customers are at the heart of everything you do.
Finally, after conducting the right segmentation and personalisation based on actionable data, what is your message? It must have a different tone for different targets, and consistency across channels without being overly repetitive. You must also choose how to deliver it, from words to visuals, audio and/or video. Essentially, to manage and integrate the right content with your chosen channels, the tech needs to be supportive. If your content and asset management systems are integrated with your marketing automation, efficiency and consistency are achievable.
All the above basically come down to the following trichotomy: data, content and channel delivery. Each of these domains has a matching tool-set, often affected by different teams, skills and budgets and can be used as a top level model for consulting.