To put a finer point on the issue, Forrester projects that global spend on marketing automation will continuously increase by about 2 billion EUR annually. And much of these funds will be invested in the trends detailed below.
Understanding the goals of customers and keeping them involved
The popularity of the waterfall model has dwindled over the last 10 or 15 years. In this approach, each phase — design, planning, implementation, testing etc. — is separate. In digital projects, the customer is often included in the planning phase, but communication during implementation can be scarce.
In contrast, Agile has become increasingly attractive across industries in our digital world. Regardless of the methodology used, close customer co-operation can benefit all businesses. Especially in Marketing Automation, the goal of product owners is often to reach their end customers in a more meaningful way, while finding new leads and converting them into sales. By using different platforms and technologies, the latter can be achieved.
In 2019, more than before, it is no longer feasible to keep a product owner at arm’s length during project implementation. The targeting, acquiring and nurturing of end-customer needs to be aligned with the strategy and vision of the product owner. This can only be achieved through close cooperation with the product-owner throughout all project phases. Therefore, for marketing automation to be successful, understanding and involving the customer is crucial.
Prioritize more relevant, more personalized content
According to one recent study 29% of B2B marketers use personalization in their marketing strategies, whereas 49% find it effective. Optimizing content that is intended for a specific audience can certainly have a positive effect on the customer journey. Regardless of the format of the content, its relevancy and benefit to the reader play a significant part in engaging customers. Personalized, optimized and well-targeted content can shape customer interactions with the product.
In other words, instead of marketing to everyone, marketing automation allows you to connect with your ideal customer. One of the most effective ways to achieve this is through personalized content. Naturally, before optimization can take place, knowing and identifying your target audience is critical for content customization and targeting.
There are tools available online that can analyse and harness data from social behaviour, consumer choices, and previous purchases to personalize content. If a customer purchases a specific product, then one way of catering to his or her needs and interests might be delivering content on how to maintain that product.
Integration of Cross-Channel Marketing
Brands that engage clients through multiple-channels have been shown to achieve an average loyalty retention rate of 89%. Nowadays, the way consumers shop can span multiple channels — and devices. Somebody shopping online may be interested in a product, but make the purchase at a physical store, and this journey can happen the other way around, of course. Ideally, a true omnichannel marketer ensures that each channel provides a seamless experience, as the channels are interconnected.
Therefore, a well-implemented cross-channel marketing strategy is much more likely to succeed than a series of single-channel strategies. Even though a multichannel presence is important, identifying key channels is crucial. The right approach or the right combination of channels may differ with the service or product that is being marketed. Compared to a single-channel approach, the incorporation of mobile, email, social media and content marketing channels will engage the right users with the brand and boost sales.
AI and chatbots
It all comes down to personalization. Dynamic content based on manual segmentation is no longer sufficient to engage consumers. Utilizing AI is a scalable way to provide unique experiences. AI has driven increasingly more efficient data analysis, which is needed to personalize experiences. Accordingly, AI can make smart suggestions about content for all journey stages, leading to its hyperpersonalization and the creation of unique journeys for customers.
One of the potential use cases for AI is chatbots, which are here to stay. The demand for real-time customer service is driving the need for chatbots, as humans cannot answer every single query. The integration of chatbots into websites and social media platforms in addition to traditional customer service is also a way to gather data for later use in marketing efforts. Whether an organization needs a simple customer service assistant to provide data-related answers or an online salesperson to promote offers, AI should be considered.
Today, predictive lead scoring is using models to integrate data from customer relationship management, marketing automation tools, websites, social media and third-party sources to identify patterns and relationships around successful leads for use by marketers. By combining the characteristics of successful leads, predictive scoring identifies “hidden” buying signals that are nearly impossible to find with traditional rules- and logic-based lead scoring.
AI is becoming more accessible, but the quantity and quality of data remain key. Predictive lead scoring offers the biggest benefits to companies with larger datasets, but these can be harder to analyse. Therefore, predictive lead scoring utilizing AI helps to pull more signals from that noise to determine which attributes are significant and which are irrelevant. It also reduces human error and bias in lead scoring. Real-world examples are showing increased productivity in sales activities, efficiency in marketing-sales cooperation as well as higher win rates by using these solutions.
Success metrics redefined
The cost of generating new traffic is higher than getting more out of existing traffic. The attention of existing and new customers is also continuously becoming harder to attract, as information and distractions continue to increase. Businesses must therefore recognize the investments of effort their services require from users — and figure out ways to minimize this factor. This focus should also be reflected in metrics and KPIs used to measure the success of marketing efforts. Companies need to find alternative ways to measure customer and conversion success that are not purely based on engagement, but instead prioritize long-term value.
However, spreading the customer experience across multiple channels makes it harder to determine which channel or audience should get the credit for reaching certain goals or conversions. Attribution models and technology will play a bigger role in understanding the value of different channels. A holistic view of customer engagement that draws from marketing automation platforms may help with examining successes across different channels.
The future belongs to robots… and humans
A high level of automation does not necessarily mean a satisfying customer experience. As technology and automation evolves, one of the challenges will be staying true to your brand voice. When the data tells everyone to do same things, humans are needed to keep brands authentic and emotional.
Marketing automation can provide an excellent basis for customer communication, freeing up time for marketers and support teams to be creative and provide exquisite levels of customer service — the human touch at the front line. As marketing is not only a science but also an art, finding the proper balance between data-driven automation and ingenuity of humans will be crucial. Fortunately, the machines will not be entirely replacing us in 2019.
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