Consumer services have to be highly convincing to their customers, especially when consumers are craving personalized approaches. According to Allegra, 77% of consumers have paid more for a brand that provided a personalized experience and companies are responding accordingly.
It’s time for consumer service and consumer experience markets to catch up for their own good. As Gartner suggests, by 2020, smart personalization engines used to recognize customer intent will enable digital businesses to increase their profits by up to 15%.
Consumers want to be noticed and recognized. In this blog post, we’re looking at 3 Use Cases of how companies who sell services or experiences can step up their conversion game by personalizing visitor journeys on their websites.
Use Case 1 - California Academy of Sciences
California Academy of Sciences is a natural history museum in San Francisco that is among the largest museums of natural history in the world, housing over 26 million specimens. The museum is known for its daily exhibits and wildly popular Nightlife Event. This event makes science more approachable for different generations by combining discovery and fun. On their website, you may book daily exhibition tickets, Nightlife tickets, become a member, engage with educational content and more.
California Academy of Sciences Homepage
Let’s outline a campaign for calacademy.org that will attract attention to the Nightlife event based on what content a visitor was engaging with. Here’s how we harvest intent at calacademy.org and use it to convert visitors into customers:
- Collect and store data. First, let’s store every interaction by a visitor to understand their behavior. Imagine that we’re collecting data from marine-oriented exhibits and articles. Based on a visitor journey intercepted via predictive modeling, we can tell that a visitor is highly engaged with the marine section of the website in a marketer quantified way.
- Create visitor segments. We specify a target group by blending past behavior (fact) and future behavior (predicted). For example, we target visitors who during one or multiple sessions are reviewing at least 3 marine-themed pages (behavioral property Count of). The visitor is predicted to drop off without purchasing a ticket (predictive property Will Not Do). Based on Visitor Journey Analytics, we know that the visitor has not been to the Nightlife event (behavioral property Has Not Done), so we market the Nightlife event from an angle that would interest a marine enthusiast. Here’s what our future segment looks like:
Segment inside Intempt
- Time to campaign! We create our future campaign in 6 steps by specifying a targeted segment, campaign goal, preferable channels of communication, notification message, and delivery preferences. For example, According to alexa.com, average number of pages a visitor browses on calacademy.org is 2.8. Therefore, 2 or 3 pages delay should be also reasonable for a notification. Final look:
Simulated Scenario - Predictive Notification (framed)
Why this notification at this time?
- They have engaged with at least 3 pages of marine-oriented content;
- They are not aware of the Nightlife event;
- They are predicted to drop off without converting into a customer.
In this way, we declutter the website from unnecessary notifications by delivering only those notifications that are tailored to the visitor’s preferences.
Use Case 2 - Roger CPA Review
Roger CPA Review is on a mission to ensure the study process is effective, efficient and enjoyable for aspiring CPA’s. The company offers a range of products such as Select, Elite, and Premier Course Packages, as well as a free CPA trial. Educational hub attracts nearly 170,416 unique visitors each month, which is an opportunity for marketers to personalize their interactions and convert them into customers.
Roger CPA Review Home Page
Considering the price of the Course Packages, such a purchase may seem as a big commitment for first-time visitors. A longer consideration period requires active nurturing; therefore, in this case, our goal will be to capture visitor data - sign up for a free trial - in return for a small commitment. Here’s how we get there:
- Store data. Once we install a tracker on the company's website, the platform is using auto-tracking as opposed to manual tracking of the data. This means that data is not going to slip away and will be stored for potential future use. We pay close attention to data collected from pages that get visitor acquainted with company’s Course bundles and CPA exam structure.
- Segment the audience. We create a sophisticated segment for a visitor that got into the funnel but didn’t make it to the end of the purchase. In particular, we’re looking at the first-time or returning visitor who has reviewed the price of Course Bundles (behavioral property Has Done), got acquainted with exam structure, specifically AUD and BEC sections (behavioral property Has Done), has not signed up for a trial (behavioral property Has Not Done) and is predicted to drop off without signing up (predictive property Will Not Do).
- Campaign to prevent drop-off. For this campaign, we’ll attract the visitor’s attention to success stories of students who have already passed exams our visitor was inquiring about. We know their interest based on what pages they have browsed. In this case, we’re pulling them through the funnel instead of letting them leave the website.
Our future notification:
Simulated Scenario - Predictive Notification
Why this notification at this time?
- The visitor is aware of the course prices but hasn’t signed up for them;
- The visitor has checked out specific exam types;
- The visitor is predicted to drop off without converting into a subscriber or purchasing a course.
Once the visitor is on Justin’s story page, we send a notification to engage with a free trial by requesting a small commitment (their email with no credit card data) and link them to the Free Trial page.
Now that we now the visitor's intention, it’s an appropriate time to send a free trial notification and avoid pop-up messages.
Use Case 3 - Blurb.com
Blurb is a self-publishing platform allowing individuals to create, publish, share, promote and sell their own books. Authors can then share and sell their book directly from their website, blog, or social network via Blurb's Direct Sell.
While Blurb’s homepage is beautifully designed, you’re immediately exposed to two notifications that offer a discount - 20% off for a sign up and 35% off through November 1st. In this case, we’ll use personalization to lower the CPA for Blurb and show discount notifications to convert visitors who are predicted to leave the website without converting. This is how we swap one-size-fits-all marketing, reserving that money for those who are inclined to covert - all while they are on the website, thereby minimizing retargeting ads:
- Gather data. In Blurb’s case, we’ll collect data on the website’s Photobooks section. According to Alexa.com, keyword “blurb photo book” is the most popular keyword that attracts visitors to the website. Also, the discount code of 35% is targeted at photobooks. Blurb’s efforts are on Photobooks, and we want to ensure high conversion rates there.
- Identify a drop-off point. We’ve assumed that visitors leave the website after they choose a photobook service and proceed to upload their PDF. Before the visitor uploads the pdf, this form appears, gating the funnel:
Gated Photobook Print
As we know, commitment oriented forms tend to prevent visitors from moving through the funnel. To back our hypothesis with data, we slice two narrowly defined segments out of the funnel and compare how many visitors have fallen into each segment. We create a Segment 1 for visitors who visited the Form page (behavioral property Has Done) and a Segment 2 for visitors who visited the page that follows (behavioral property Has Done). Here’s what it could look like:
Segment 1 audience vs Segment 2 audience (marked in red)
Based on the gap we noticed between the two segments, we know a visitor is likely to leave, so we prevent the drop-off with a targeted notification.
- Segment our visitors. For this segment, we are focusing on first-time or returning visitors who haven’t subscribed (behavioral property Has Not Done), reached the form step (behavioral property Has Done), and are predicted to drop off without subscribing (predictive property Will Not Do.)
- Time to campaign! For this campaign, the visitor reaches the form, we know the possibility of a drop-off is high based on the segment we previously saw. It’s a good time to send a notification inviting them to use the discount code and incentivize them to sign up. Using Campaign Editor, we specify a targeted segment, campaign goal, preferable channels of communication, notification message, and delivery preferences. Final look:
Simulated Scenario - Predictive Notification
Why This Notification At This Time?
- The visitor has engaged with Photobook creation;
- The visitor is new to the subscription;
- The visitor is predicted to drop off without becoming a subscriber.
In this scenario, we’ve leveraged a visitor’s intent to create a photobook and lowered the CPA by incentivizing only those visitors who are predicted to not reach the final funnel step.
Consumers need you to anticipate their needs - even before they have specified a thing on your website. Equipped with data modeling, visitor journey analytics and predictive personalized notifications, marketers are now in control of consumer journeys.
Looking to increase your conversion rates by delivering personalized experiences?