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The current crisis is provoking many conversations around content, brand voice, and frequency of messaging for marketers. According to Litmus, only a quarter of email marketers feel confident they have a solid communication plan right now.
These are the three questions front of mind when communicating with customers:
What are we trying to communicate?
How do we provide support and empathy?
How do we field calls from anxious customers?
One of the challenges in developing messaging during the pandemic is customers have different needs and personalities. In today’s climate, you have to channel your sixth sense: empathy. You must rely on their understanding of their customers and themselves during life’s most stressful events.
There are tools that can help marketers achieve this level of personalization at scale. Artificial intelligence (AI) can tailor the content, timing, and frequency of messages. It delivers insights and allows marketers to be proactive in improving customer experience.
You can use AI to:
Adjust the timing and frequency of each message
Discover the right sentiment and language for each customer
Automate personalized content and imagery
Read on for more detail on each.
Orvis, a sporting goods retailer, uses Einstein Send Time Optimization (STO) to ensure they send messages when customers are most likely to read them. With inboxes being inundated with emails, Einstein STO raises the chances your message won’t get lost in a recipient’s inbox. Orvis found the ideal time for them to deploy emails to each customer. STO is their first step in creating a total personalized customer experience.
With STO, you can:
Improve engagement and conversion KPIs with your emails by sending at the time each customer is likely to engage
Beat out the competition and be at the top of the inbox when your customers are more likely to be engaged
Save time and automate manual filter and query processes often used to achieve send time optimization
Even with Send Time Optimization, you don’t want to alienate your customer base by emailing too much. If you’re an Einstein user, the Einstein Engagement Frequency dashboard shows send volumes compared with engagement for a given period of time. It provides suggestions on the optimal range of emails to send that maximize engagement.
Determine which subscribers are over-engaged and which subscribers are under-engaged
Create segments based on the insights from the dashboard
Personalize a send strategy for your over-engaged subscribers versus your under-engaged subscribers (such as creating a promotion for under-engaged ones)
AI surfaces insights to help marketers improve the customer experience. It can use data to alert the marketer about performance and suggest areas to improve. Sentiment analysis goes beyond topic detection and focuses on whether the response to the message is positive, negative, or neutral. Language insight brings emotional tone into the mix. Tone is more granular than sentiment – it includes things like love, anger, disgust, and surprise. You can decide the tones you’d like to capture through machine learning.
Tone and language insights can also drive email opens. AI can identify the tone, words, and phrases that resonate with customers at scale. Gathering these insights can help develop an overall messaging style for email content and other communications. It can also help marketers group customers based on how they respond to different sentiment and language. Einstein Sentiment Insights and Einstein Copy Insights understand how sentiment, tone, and language impact your customers.
If you’re working to set up your own sentiment analysis, here’s a tip: a machine learning-based approach for sentiment analysis and language insights requires a collection of documents (sentences and words), each manually evaluated and labeled in terms of sentiment.
Training data is the most important part of developing your sentiment analysis and language insights. Brands need to embrace the valuable data specific to their industry and customer.
The most valuable data you have are your customers, so understand how to capitalize on what you already know and use it for machine learning training.
AI helps you choose the right content to complete a fully personalized customer experience. Marketers can create an asset pool and use machine learning to display the right image to the right audience upon opening the email. For example, a customer who is located in an area without shelter-in-place restrictions will relate to different imagery than a customer living in a location with shelter-in-place restrictions.
“Email plays a huge role in the customer experience, starting with understanding our customers through deciding what we should be talking with them about,” says Tim Delles, Senior Manager for Email Strategy and Innovation at Orvis. “In a time when staying connected is so important, Salesforce's AI-powered content selection feature allows us to create meaningful and highly personalized conversations with our customers.
“We’re an experiential outdoor brand,” he adds. “We’ve been able to rethink our approach to email as we continue to find new ways to deepen meaningful relationships with our customers during the current context.”
Einstein’s Content Selection makes a marketer more efficient by:
Removing the need to build out multiple versions of emails
Picking content from a specified pool to ensure each segment receives an image that tells a story
Driving personalized conversations with customers
The Orvis team combines Send Time Optimization with Einstein Content Selection to drive customer engagement. It also helps them with internal collaboration. Ai allows the Orvis team to focus on building a strategic content pool versus building out email after email, making it easier to collaborate as they continue to work remotely.
Learn more about AI by taking the Einstein for Marketing Cloud Basics trail.
