Tricky questions like “what do you want to be when you grow up?” prompt journeys of discovery. There is no “right” answer when choosing a career; it all depends on the individual. This is why college students take random classes that sound fun and work internships with endless coffee runs. At each step of the way, they’re gathering information to determine that perfect choice.
Marketers go on similar journeys of discovery to answer questions. “How do we boost click throughs for this particular social media ad?” or “how do we decrease cart abandonment?” are going to have very different answers from one business to another.
Much like a college student trying various classes, getting feedback and then selecting a suitable first job, marketers also employ methodical trial-and-error. Formally called A/B testing, this is a scientific way to verify a hypothesis. A/B testing involves randomly splitting prospective customers into different groups, then altering one campaign variable at a time. Based on the observed results, intrepid marketers can conclude what works best and chart the way forward. Thankfully, this process is much faster than the self-discovery required to select the right career.
If you’re a Salesforce Marketing Cloud user, you’ll be pleased to hear this platform offers multiple avenues to pursue A/B testing. Keep reading to learn about the benefits your team can reap from this technique and get specific examples pertaining to Marketing Cloud tools:
The first notable benefit of A/B testing is circumventing internal conflicts. As marketing involves abstract creative elements, it can be challenging to decide on a plan. Team members make recommendations based on their own experiences and understanding of the target audience.
For instance, one designer could champion a skeuomorphic look while another favors flat design. An email marketer could suggest using recipients’ first names in a message to increase open rates, while another disagrees.
A/B testing provides a concrete way to validate these hunches with data. Teams can scientifically test both options to determine the strategy best suited for their target audience.
Over time, A/B testing creates a comprehensive, data-validated picture of what a company’s targeted customers prefer. Marketers empowered by data can dig into both customer attributes – unique details like gender, geography and credit scores – and customer behaviors such as favored creatives and discounts. All this analysis means marketers can ascertain what makes their customers tick at any point in time. Better customer understanding, in turn, leads to increasingly precise targeting and more successful campaigns.
Of course, campaign end goals vary depending on company and industry. A wealth management firm may simply want customers to read a quarterly report, while an online retailer wants customers to complete purchases. Some businesses have layered, complex goals. For example, the creators of a food delivery app want new users to download the app and create accounts. After this initial goal is met, the company might wish for the typical customer to place an order at least once per month. Regardless of the industry or business, the better the customer data, the more likely marketers are to sway their audience.
Lastly, A/B testing fosters a culture of continuous research and improvement. Once a team adopts a data-infomed mindset, there’s no going back to guesswork and hunches.
Think about the people you know who are dedicated to careful reflection and self-improvement. Such individuals learn what they can from every situation and use those lessons to be better in the future. You probably used this same mindset to find the job you love or figure out some other tricky quandary. Learning and sustained progress are ingrained in the discipline of A/B testing. Imagine an entire team working this way every day, all in the service of the customer.
Let’s dig into concrete examples of A/B testing, all possible with the different tools on the Marketing Cloud platform:
Consider an online retailer sending a promotional email. This marketing team aims to promote a new clothing line specifically to male customers. Using Email Studio, they can set up dynamic content whereby half the recipients will see one version of the banner image, while the other half will see another. The recipients in each category are selected randomly, ensuring accuracy. Now, the marketers can review which design style most resonates with their male customers. In future emails, they can play with different banners, subject lines, headers and footers, testing everything from copy to visuals to personalization tokens.
Note that A/B testing is done by changing one variable and keeping everything else constant. This proves or disproves a specific hypothesis. On the other hand, if the team changed both the subject line and the banner image, they couldn’t be sure which variable was causing their audience to respond.
Journey Builder gives marketers the freedom to experiment with more comprehensive strategies. For instance, a marketer for a financial daily newsletter is striving to boost the percentage of people who verify their email post-registration.
The status quo is to send a confirmation email six hours after the initial customer signup. The marketer hypothesizes that this wait contributes to big drop-offs in email verification. She creates random split customer journeys: for four weeks, 30% of new subscribers will receive their confirmation email right away. At the end of the month, the marketer has collected data from 100 customers who were assigned these different paths randomly. She can now confidently report her findings, proving that shorter email wait times lead to higher rates of verification. Next, the marketer applies this insight to other campaigns as well.
Speed is also noteworthy when it comes to Journey Builder. Marketers can quickly spin up new paths for customers and observe the results. For example, a marketer can experiment by sending customers who abandon carts a discount offer. When someone returns to their cart and uses the discount credit, Journey Builder automatically tracks the activity. This tool keeps up with rockstar marketing teams and accounts for the entire customer experience.
All marketers are familiar with social media campaigns. But clearly pinpointing why any given campaign performs well isn’t always easy.
This is where A/B testing saves the day. For a particular Facebook ad, a clever marketer could set up a 50/50 split, displaying different versions of the creative (perhaps the brand is experimenting with competing design philosophies). At the end of a set timeframe, Salesforce delivers a revealing count of how many people clicked on each ad.
Thanks to UTM tracking, the marketer can visualize the sales funnel, from ad to landing page to cart to the final order confirmation page. Just as professionals benefit from in-depth feedback on their work performance, marketers need granular data on their campaigns. This kind of insight hones in on potential problems; maybe clicks drop off at the landing page stage. Armed with this knowledge, the marketer can formulate a hypothesis and begin the process of finding the optimal solution with – you’ve guessed – additional A/B testing.
Unlike in a person’s life, where the individual might pursue a course of action, then reevaluate and change gears, A/B testing moves fast. Marketing teams don’t have to wait to complete one strategy, then another – both can be done simultaneously and compared.
Interaction Studio (currently known as MC Personalization) is unique because it offers additional sophistication and flexibility. This tool tracks users – even ones that haven’t shared names and email addresses – using beacons that follow activity across a company’s entire site. Since these beacons monitor every single click and scroll on a landing page, businesses can delight customers with customized experiences.
Think of this as automatic A/B testing, where an algorithm decides what to display as opposed to a marketer trying out a hypothesis (marketers can command full control at any time). For example, a customer visiting a sports gear website sees an ad for discounted women’s running shoes. Although this customer hasn’t shared her information with the company yet, the beacon recorded her past browsing history of women’s running-related products. Of course, the personalized offer is more likely to resonate.
Salesforce’s nifty algorithm can personalize every part of a website for the customer’s convenience. On the same sports gear site, a registered member who enjoys kayaking might see an ad for kayaking events specifically in his hometown. This ad is further tailored both to his preferences and the page he’s browsing, which relevantly displays a wetsuit.
Behind the scenes, marketers must label and categorize all the site pages so the system understands the content of each one. Once this is done, they can also feed data from previous A/B tests to further contextualize real-time customer behavior. Interaction Studio will deliver the most personalized experiences with the least amount of hands-on effort from marketers.
A/B testing is much more than a trendy tool to add to the marketing repertoire. It represents a scientific and precise mindset. Marketers stand to gain a deeper understanding of their target audience and keep up even as customers’ preferences change.
Don’t be daunted by the never-ending nature of A/B testing. It’s meant to be an ongoing process, just like answering any of life’s tricky questions requires constant analysis and re-adjustment. Happily, Marketing Cloud offers an easy entry point into this discipline.
With Marketing Cloud, A/B testing tools are all in one place. Marketers can quickly visualize the results of their campaigns, playing with different ads, pathways and user experiences. If you’re ready to begin your own journey of discovery, Accelerize 360 can help.
Let’s get to the bottom of those marketing quandaries together.