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How to Leverage Data to Optimize Marketing Automation
- 1. How to Leverage Data to Optimize Marketing Automation Braydon Unsicker Tinuiti @Tinuiti
- 2. Braydon Unsicker/Tinuiti @Tinuiti 600+ Employees $1.5B Managed Media Spend 10 Offices Around the U.S.
- 3. Agenda 1. Defining Marketing Automation 2. The Data That Fuels Marketing Automation 3. Ways You Can Collect Data 4. Automation Examples 5. What’s Coming 6. Resources Braydon Unsicker/Tinuiti @Tinuiti
- 4. Let’s Get on the Same Page Braydon Unsicker/Tinuiti @Tinuiti
- 5. Marketing Automation Marketing Operations CRM & Email Marketing Braydon Unsicker/Tinuiti @Tinuiti
- 6. CRM & Email Marketing Reviews Repeat Sales Time in- app Nurture Cross Sales Braydon Unsicker/Tinuiti @Tinuiti
- 7. Data That Fuels Marketing Automation Braydon Unsicker/Tinuiti @Tinuiti
- 8. Marketing Automation Ad Engagement Persona Profiles App/Product Usage Purchase History Browsing Behavior Content Engagement Demographic Data Account Data Braydon Unsicker/Tinuiti @Tinuiti
- 16. Automation Example #1 - Udemy Braydon Unsicker/Tinuiti @Tinuiti
- 17. Udemy User Journey Braydon Unsicker/Tinuiti @Tinuiti
- 18. My Udemy User Journey First Course Purchase Confirmation Email 2020 Planner Related Course Promo Wait 1 day Wait 6 days Related Course Promo Add to Calendar Sends Braydon Unsicker/Tinuiti @Tinuiti
- 19. Optimized Udemy User Journey First Course Purchase Confirmation Email /Getting Started How to get the most out of your course You’re on a Roll Wait 5 Days / 25% Done Jump Back In Survey / Recommended Courses 5 Days 25% done Wait 6 Days / 75% Done Not The Right Course? 10 Days Not Started Wait 5 Days / 25% Done 5 Days Not 25% Done Braydon Unsicker/Tinuiti @Tinuiti
- 20. Automation Example #2 - Bombas Braydon Unsicker/Tinuiti @Tinuiti
- 23. 100% Increase in Email Revenue 100% Increase in Subscribers 56% Increase in Monthly Conversions Braydon Unsicker/Tinuiti @Tinuiti
- 25. Artificial Intelligence & Machine Learning Braydon Unsicker/Tinuiti @Tinuiti
- 27. Guides: ● Cart Abandonment Strategies for Email Marketing ● Better Together: Email & SMS Marketing Guide ● Email Marketing Strategies for the Modern Marketer Careers: ● https://tinuiti.com/careers/ Braydon Unsicker/Tinuiti @Tinuiti
Editor's Notes
- Hey everyone, as was mentioned, my name is Braydon Unsicker and I am really happy to be here. I'm a big fan of Stukent and love what they’re doing and am glad they invited me to chat about leveraging data to optimize marketing automation. Marketing automation can be a very powerful part of any marketing program, but from my experience I’ve found that it is often underutilized or underperforms because companies are not leveraging their data to inform their programs. I hope we can change that for the companies you work for or will work for.
- Before we begin, I wanted to add a short plugin for Tinuiti. We’re the largest independent digital marketing agency across the triopoly of Google, Facebook, and Amazon and I’m really proud to work here. Tinuiti takes great care of their employees and I think that’s a big portion of why we have been so successful. We are always on the lookout for new talent and hiring for internships and other positions so check out the careers page on our website if you’re interested.
- Marketing Automation uses software to personalize experiences for your audience with relevant and timely messages. It’s what transforms mass marketing into personalized 1 to 1 experiences. It can be broken into two main functions. Marketing Operations and CRM & Email Marketing Marketing Operations would include things like lead scoring and lead management while CRM & Email marketing is where you set up triggered emails, set up nurture campaigns, and do list segmentation to help leads on their path to purchase and beyond. My presentation today is going to focus on how to use data to optimize the CRM & Email piece of things.
- When it comes to CRM & Email Marketing - At its core, it’s retention marketing, a way to keep people coming back. Coming back for more content, first purchases, repeat purchases, cross-sells, reviews, time in-app, etc. by utilizing data to curate communication that is relevant and timely. People usually don’t immediately make the connection with their needs and your solution and need more time and information before they decide if they need your product. That’s where CRM & Email marketing comes in and thrives. It’s a way to meet your prospects and customers where they are and message them on a 1 to 1 basis that helps them take the next appropriate action. There are so many ways CRM & Email can be leveraged to help brands get more from their prospects, customers, and marketing campaigns. I hope my presentation today inspires you to think creatively and come up with ways you can use data to create great experiences.
- Depending on the business model and the sophistication of your martech stack, there are lots of different data sources you can use to optimize your CRM & Email efforts. Here are a few general examples of data sources you can pull from. Demographic Data: Age, Gender, Title Content Engagement: What videos are they watching or what guides are they downloading Account Information: Employee count, revenue Persona Information: Pain points, objections, needs App/Product Usage: Build triggers of things they do or don’t do. Ad Engagement: Engagement with emails, social ads, Google ads Purchase History: What are they buying, what’s their purchase rate, what offers do they respond to Browsing Behavior: What pages are they visiting, what are they adding to their cart, how frequently do they visit your site You use this data to segment your list and send them content that is relevant to them and the situation.
- A lot of the Email Service Providers out there like Marketo, Klayvio, Hubspot, or Bronto will track your customers and leads browser behavior and purchase history, but some things you need to collect on your own through forms, surveys, or data appending services. I want to show a few examples of things you can do to get more data.
- Here is an example of a great Overlay from Brooks Running. Notice how they ask for more information than just the email address. Getting important data points like this from the get-go is important to support your segmentation strategy so you can create a good relationship with them right out the gate with a more personalized experience than what just an email can give you.
- Here is another overlay example from Electric, the sunglasses and apparel company out of California. They take it one step further than Brooks did and ask for specific interests.
- Here is another example from Brooks. After you give them your email address in the footer or a few other locations sprinkled throughout their site it takes you to this preference page. I love the questions they ask, they are trying to understand your needs so they can provide relevant messaging. I’m sure Brooks has segments based on each of these questions.
- Chatbots are another way to collect data that has grown in popularity due to the instant answers and conversational experience. Facebook Messenger bots are similar to chatbots as well.
- Forms are very common, you should be very intentional about what fields you include as you can use the fields for segmentation and lead qualification. You can also trigger things based off of what the gated content piece is.
- Here’s an example of a short survey sent via email from Brooks. You can tell I’m a fan of how Brooks does things. Brooks is collecting data on you depending on what you click. This is a great direct to consumer example, but you can use surveys in lots of different ways. In a previous tech company I worked for we sent an incentivized survey to all closed lost deals asking why they didn’t purchase and depending on their answer we sent them down specific nurture tracks targeting their objections.
- I have two examples of marketing automation in the wild I want to share. To start, this is an experience I had with Udemy not long ago.
- This is a screenshot of the emails they sent me right after I purchased a course about copywriting. So I purchased a course on Jan 10, but didn’t start the course until Jan 26. Keep that in mind as we look at these emails. They sent me a confirmation email here then sent me this 2020 planner right after. The day after they tried to get me to buy a related course. And then they bombarded me with a bunch of other promotions. What’s wrong with this picture? They are trying to get me to buy another course 7 times before I even started the first course I purchased. That doesn’t make any sense, especially for a first-time buyer like I was. They should have focused on helping me consume their product and get the most value out of it before anything else. I would be much more likely to buy again if I loved the first course I purchased. You can even tell I lost interest in their emails after the first few.
- Let’s take a look at my user journey mapped out here. Notice the lack of data they are using. This is a very linear path built off of assumptions and not data. The one thing they got right was the related content part, they did send courses I would be interested in. But an accurate recommendation at the wrong time is no good and that’s why I didn’t buy another course.
- Here’s a proposed user journey using data to optimize the experience - Some of the data I used when putting this together was Purchase History (this should only trigger for first time buyers). And I used product usage data to determine timely messages to help them get through the course. Then, once they helped me through my first course they could send a survey to collect more data and ask questions like what do you want to learn next. If they don’t respond to the survey then they can send related courses based off of purchase history.
- Now let’s look at a better example from some work Tinuiti did for our client, Bombas.
- For Bombas we used data from the users brand engagement like browser behavior, email engagement, and purchase history to segment their list and adjust the number of emails each segment received each week. For example, those who engaged more frequently with their emails and website were sent more emails than those who didn’t. This decreased list attrition while simultaneously increasing email engagement.
- In addition, we set up a few sets of triggered emails based on their site behavior like a cart abandonment series, win-back emails for customers who haven’t made further purchases in a given timeframe, and browse abandonment emails to entice back shoppers who considered items but left the website without adding them to the cart.
- Here were the results
- Artificial Intelligence and machine learning are going to have a huge impact on the optimization and scalability of automated campaigns. ESPs and other marketing tools are going to be able to “learn” how and when to communicate with prospects and customers in a more personalized way than was ever possible before. For example, let’s say that a customer named Alec is expected to purchase every 30 days, but another customer named Oakley is expected to purchase every 90 days, then messages can be targeted for their unique timing, rather than a generic 45 days for all customers. Essentially, data that was difficult to capture before AI will now be much easier. Things like predicted customer lifetime value, spending power, and preferred communication channels will better inform the automation programs we set up. Already, some ESPs and other marketing tools are starting to incorporate AI powered segmentation, but I bet we start to see new ones that are built with AI at the center and they will begin to replace the ESPs of today.
- And finally, I have a few resources I want to give you all.
- These are a few guides that take a deeper look into how you can utilize CRM & Email marketing that Tinuiti has produced. They are really good and suggest you check those out. And I added a link to our careers page here as well.
- That’s it, thanks again for having me and I welcome anyone who would like to connect with me on LinkedIn to chat further.