5 Marketing Automation Mistakes You Might Be Making and How to Fix Them
Seventy-five percent of marketers currently use at least one type of marketing automation tool, and spending on marketing automation is expected to hit US$25.1 billion by 2023. However, despite its widespread use, this type of software is not being used to its full potential.
Lack of a clear strategy, using too many or too few tools, and not testing and tracking your efforts are some of the obvious pitfalls. On top of these, here are some less apparent marketing automation mistakes you might be making – and how to fix them.
Mistake #1: Not Using Your Valuable Data
Data is vital in any marketing automation strategy. However, you can’t use it to drive your efforts if you aren’t collecting and using all your valuable data.
The Fix for You
What is your valuable data? It includes all demographic, behavioral, transactional, and qualitative data from your e-commerce sites, web forms, official websites, apps, CRM, social media channels, customer services and more.
Marketing automation platforms can collate this data in real time for a complete customer view. Such insight allows you to segment your audience in order to create more relevant, personalized content.
Ninety-one percent of customers say they are more likely to shop with brands that deliver relevant offers and messaging. In addition, personalization can boost revenue by up to 15 percent. Therefore, using the data-driven insights to personalize your efforts makes sense.
Mistake #2: Selling, Not Nurturing
When you have the option to automate, it is easy to start pushing sales messages out there. However, bombarding your audience with promotions isn’t going to win you any hearts or wallets. In fact, people will likely get fatigued and send you straight to spam.
The Fix for You
To avoid this, instead of adopting this sales-led approach, be sensitive to what stage of the buyer cycle your prospects are at, and tailor your messages accordingly. By sending automated content that fits their needs at each stage through channels such as web push and SMS, you can push them along the funnel towards purchase.
At the awareness stage, people are looking for answers, resources, knowledge, opinions, and insights. To meet this need, send out helpful information such as links to problem-solving blog posts and social content.
The middle or consideration stage can be fairly short in B2C. For example, it may not take someone very long to decide on a pair of sneakers. However, someone buying a car will likely take longer. In both cases, your focus here should be on building trust with things like instructional videos and product specs.
At the conversion stage, it is all about validating decisions, so send personalized product recommendations or ask them if they have any questions. You should also send automated messages based on actions, such as to people who have abandoned carts.
Mistake #3: Failing to Be Human
While marketing automation is a great efficiency driver, if your content sounds lifeless, robotic, and doesn’t tap into a customer’s needs and wants, your efforts won’t be well-received.
The Fix for You
It is important to remember that even though you are sending triggered messaging via a machine, people on the receiving end are human. To build trust and relationships, humans need warmth, genuine connection, and to feel valued, so ensure your automated content conveys this.
Firstly, personalize your content by tailoring your recommendations, text and images to personal interests, preferences and behaviors. With additional help of machine learning tools, you can even predict future behavior for hyper-personalized experiences.
Secondly, make sure your automated messaging is timely. For this, you can use cross-screen insights to map your customers’ fragmented journeys allowing you to send the right message at the right time on the right device.
By connecting and communicating with your audience at this individual level, your automated messaging will be more engaging and more human.
Mistake #4: Taking a Single Channel Approach
It is likely your company has multiple customer touchpoints, from your website and apps to your email, SMS and social media. But how many are you automating? And are your efforts consistent across them all?
While you might have set up automated emails or in-app messaging, if these communications don’t take into account the other interactions a customer might have had with your brand in the meantime, you risk getting the messaging wrong.
The Fix for You
By adopting a multichannel approach to your marketing automation, you can avoid this. Leverage the data from your online and offline touchpoints to connect the dots and see which channels that customers respond well to, in order to deliver seamless, timely communications across all the touchpoints.
Research shows that taking this type of multichannel approach to marketing automation can improve revenue by 15 to 35 percent, app retention rates by 46 percent, and conversion rates by 49 percent. Using integrated marketing automation platforms also makes the logistics of managing your automated efforts across teams much simpler and more cohesive.
Mistake #5: Focusing on Quantity, Not Quality
One of the temptations of marketing automation is to see it as a numbers game. In other words, the more communications and promotions you send out, seemingly the better. While this sounds good in theory, in practice, this batch and blast strategy isn’t very efficient.
The Fix for You
You know the general rule that 20 percent of customers drive 80 percent of profits? Well, apply this to your marketing automation strategy. Instead of spreading time and resources across your entire customer base, work out who your top 20 percent, or most valuable customers, are and focus your efforts here.
Leverage deep learning to figure which customers have the highest customer lifetime value (LTV) by identifying behavior patterns, segmenting them into lists, and then ranking them according to their potential to bring in profit.
Once you have pinpointed these high-value customers, you can then focus your efforts on increasing your engagement with them. This means finding ways you can connect with them in between purchases to grow their emotional connection with your brand.
According to a recent study, companies who improve engagement can boost cross-sell revenue by 22 percent, up-sell revenue by 38 percent and order size by 5 to 85 percent. Therefore, the more you focus your marketing automation efforts on your most engaged customers, the better your results and ROI.
Marketing automation is not just about creating efficiencies. It is about having the ability to provide customers with a more personalized experience. By avoiding these mistakes, you can engage and nurture your prospects through the funnel with more human, insightful, and seamless interactions – the kind that drive profits.
* Do you want to improve your marketing automation efforts in 2020? Download our latest white paper ‘The Ultimate Guide to Supercharge Your Marketing Automation With AI’ for more in-depth insights. Got more questions? We are here to help! Get in touch with our experts today for an exclusive consultation.
WE ARE HERE TO HELP
YOU MIGHT ALSO LIKE
The subscription e-commerce market continues to see rapid growth, with McKinsey’s latest figures suggesting it now totals between US$12 billion and US$15 billion in the US alone. Alongside the big global players, such as Hello Fresh, the Dollar Shave Club, and Naked Wines, are an increasing number of smaller, more localized brands such as LookFantastic, Pint Society and Japanese furniture and interior goods provider Muji. Despite the growing popularity of brands such as these, subscription companies typically face high churn as they struggle to keep customers over time. So, what can subscription brands do to prevent and reduce churn? What Is Churn? Churn is the percentage of customers who stop using your products or services within a specific time frame. According to Recurly, a global subscription billing management company, the overall churn rate for subscription brands is 5.6 percent with subscription box and consumer goods running slightly higher. Customers churn for several reasons. A big one is to reduce expenses – an issue that has become more prominent since COVID-19 as people have become more conservative with their spending. Other reasons include less frequent use of a product or service, regular travel, and the seasonal nature of some subscriptions.
Author | Min Sun, Chief AI Scientist, Appier Emotion is one of the most distinguishable human qualities, one that sets us apart from machines. However, it is not out of the realm of possibilities for machines to read emotions and respond accordingly. Increasingly, machines are able to interpret human’s emotional states and adapt their behavior to give appropriate responses – something we call emotional AI, or artificial emotional intelligence (though in the computing field, it is known as affective computing). Here we will explore what it is, how it works, and how it can benefit businesses. Three Types of Emotional AI Emotional AI is the next step in the evolution of artificial intelligence. By interpreting people’s emotions, AI can respond in a much more naturalistic manner, making the interaction much closer to typical human intercourse. There are three main types of emotional AI – natural language text analysis, voice analysis and facial expression analysis. The first two are already quite common, while the third probably attracts the most media attention. Other types of analysis also include mouse movement, eye-gaze, heart rate and electrocardiography, etc. Natural language text analysis It involves AI scanning written text like a review of a
Marketing has always been highly dependent on data. And in today’s rapidly moving world, the importance of managing vast quantities of diverse data from disparate sources is growing. “There are three main issues when it comes to data management for marketers,” explains Dr Min Sun, Chief AI Scientist at Appier. “The first is data quality – the maxim of ‘garbage in, garbage out’ is critical for marketers. Once data quality is assured, the second factor to consider is the usefulness of the data. What data is valuable and which data sets can be used together? Finally, companies need to ensure they have robust governance in place. These cover the legal and corporate obligations including jurisdictional frameworks, such as General Data Protection Regulation (GDPR) in Europe, the Personal Data Protection Act (PDPA) in Singapore and others.” What Is ‘Good’ Data? There are several dimensions to data quality. Dr Sun says that issues such as consistent errors and inconsistent noise in data can significantly decrease the usefulness and value of even huge data sets. However, a more subtle issue can come even when the data is completely correct, but the assumptions underlying the selection criteria are biased or skewed. As a