How Predictive Marketing Turns Content into Revenue: 3 Retail Use Cases
Content marketing works. The right content strategy guides your visitors through the sales funnel without making them feel like you’re pitching. Your customer controls what pieces of content they interact with, while you enjoy the climb in conversion rate.
Don’t take my word for it — websites which implement content marketing are experiencing an average conversion rate of 2.9%, compared to a 0.5% conversion rate of websites without content strategy. That’s nearly a 6x increase. However, this conversion rate comes at a cost. As you look at well orchestrated content marketing campaigns from top retailers, you may wonder — how do you work your existing content to get more revenue from it? (Hint: it’s not distribution, it’s data).
Put another way, how could marketers harvest potential interest before visitors are ready to purchase? How could we turn the intent signals generated through reading articles and watching videos into behavioral campaigns that generate revenue?
Let’s walk through 3 examples of how predictive marketing tactics would drive revenue via ecommerce content.
Use Case 1 — The North Face
The North Face has a publication that an adventurer would enjoy. For modern-day explorers, there’s a section called “Explore”, which allows a visitor to flirt with the sales funnel in the manner they prefer. Some examples:
- Visitors can look for activity-specific gear under the tab “Activities” after reading content tailored to the activity in question. Check out the page “Climbing” — there’s no pushing climbing gear right away — instead we are invited to read “Breakdown of climbing styles” article, read about niche athletes or choose a local climbing destination. Products from the “Climbing Basics” line are shown, but below the fold.
- On the “Athletes” section, the visitor can select an athlete’s profile that inspires them to run/climb a little “extra”. The visitor checks out the athlete’s motivation, expeditions, videos and — most importantly — the gear they are using. It’s an elegant way of leading a visitor towards a product selection.
Content prospecting is definitely an aspect of The North Face’s marketing agenda. Browsing the “Explore” section doesn’t feel like pitching to the visitor. A visitor would convert or leave with a pleasant brand experience.
The North Face could harvest (at scale) the vast amount of intent data that such (engaging) content produces? We’re talking valuable interest data. Based on how visitors engage (and don’t engage), a marketer can anticipate the triggers that will be effective once the visitor is considering a purchase. Here are some ideas on how The North Face could potentially leverage the data to turn initial engagement into (later) revenue.
- Collect and store data. First, let’s store every interaction by a visitor to understand their behavior. Imagine that we’re collecting data from the “Explore: Athlete Team” page dedicated to Alex Honnold. Based on a visitor journey and via predictive modeling, we can tell that a visitor is highly engaged with the “Climbing” section of the website in a marketer quantified way — they’ve watched at least 3 videos covering athletes’ expeditions over the last week and are predicted to browse climbing products in the future.
- Create visitor segments. Using a platform like Intempt, where we blend past behavior (fact) and future behavior (predicted), we can specify a target group. For example, we create a segment that contains visitors who have watched Alex’s expedition videos at least 3 times (behavioral property Count of) after browsing “Climbing” section (behavioral property Has Done), and are predicted to not add a product to the cart (predictive property Will Not Do Add To Cart.)
- Set up a notification campaign to target currently active visitors from our target segment with notifications at key drop off points. In this example, a visitor may not get into the segment on their first visit of the “Explore” section. They might make it after a few visits. What happens after? If they return to the store area and browse gear, they meet a trigger event (for a campaign) which gets the notification out. Here’s what it could look like:
Why this notification at this time?
Because the visitor’s past browsing and purchase behavior and their current context is indicative of what will happen:
- They watched 3 videos of Alex’s expedition, so we use the athlete’s name in the notification to cater to visitor’s interests.
- They have browsed the Climbing section, indicating there may be an interest in climbing gear, so we suggest to pair the current item.
- The platform predicted that the visitor is not going to add an item to the cart (Will Not Do Add to Cart predictive property), so the “Free Shipping” offer appears to encourage visitor to proceed with a purchase.
Keep in mind, this isn’t blanket targeting that clutters the experience. The visitor is not exposed to a wide range of climbing pros. They are targeted with a personalized message based on the athlete with whom they have an affinity. Additionally, they are offered a shipping promotion since the visitor is predicted to not add these items to the cart based on their browsing behavior, and potentially (the model knows) their past purchasing behavior.
Use Case 2 — Levi Strauss & Co
Levi Strauss & Co invests in the “Unzipped” blog that houses their content strategy. They want to inspire their visitors instead of simply being a thin veil to their commerce. Their blog posts, that rarely link back to the store, are educational and inspiring. Levi Strauss & Co uses the blogging space to raise awareness and express their opinion on issues like sustainability, which I personally love.
As with The North Face, with Levi’s vast content library means a rich trove of useful interest data that will dictate our segment membership, campaign qualification, trigger event and eventual notification. No more data being lost in the ether- we’re gonna use it to create a richer customer intent profile. Here’s how I would turn the interest generated during the engagement period, during purchase:
- Keep collecting the data. Exploring customer’s behavior though data may tell us that existing customers were inclined to make a purchase after browsing a certain number of related pages or sharing content. The data and facts thereto deepen the customer profile.
- Let’s go back to segments — you’ve guessed it. We segment our visitors as narrowly as possible based on their activity over one or more web sessions. Imagine that a visitor who read and shared the content from “Vintage” section falls into our segment. We’re potentially dealing with folk into old school Levi’s, and it shapes our future campaign.
- Follow with the campaign. We set “Visits store” as a trigger event for our personalized notification. If a visitor falls into a segment described earlier, they are qualified to see a notification regarding a discount in the Vintage section. Moreover, we could track if they are a first-time customer and are located in a nearby area to offer them free shipping to promote new customer acquisition.
Why this notification at this time?
Because the visitor’s past browsing and purchasing behavior and their current context is indicative of what will happen:
- The visitor read/shared Vintage content on “Unzipped” blog.
- The visitor went to the store section after, which was a trigger event for our campaign.
- The platform predicted that a visitor was inclined to add an item to the cart (Will do: Add to Cart predictive property), so a discount code appears, encouraging the visitor to add an item to the cart.
Another segment we create contains visitors actively browsing the “Sustainability” section, without a clear intention to purchase. In this case, we create a campaign for store visitors who fall into a segment that includes reading and sharing sustainability content. We set predictive property “Will Do: Add to Cart”. Our trigger event would be “Browsing for clothes”. For this segment, our campaign notifies a visitor about a certain amount of purchase going to a local charity organization.
Why this notification at this time?
- The visitor read and shared Sustainability content on “Unzipped” blog. These are two fixed properties that are required to be qualified for a segment.
- The visitor goes to the store website, which is a trigger event for our campaign.
- The platform predicted that a visitor is inclined to make a purchase (Will do: Make a Purchase predictive property), so it informs visitor about funds proceeding to a local charity organization once the purchase is completed.
Based on what your visitors read, you can customize a notification that is most likely to catch their attention and flatter them in a non-pushy, predictive way.
Use Case 3 — Benefit Cosmetics
Benefit Cosmetics are pros at using content as a way to guide their users though the sales funnel. First of all, their content section called “Beauty Banter” and “Learn Brow Basics” are gems for any beauty addict — it provides tutorials, expert reviews and influencer opinions. Their Call-to-Actions are epic: “Sneak a peek”, “Meet her”, and my personal favorite — “Get influenced.”
In the “Wow Your Brows” section, “Explore Brow Transformation” is an example of how to help consumers move themselves further along in the sales funnel. The guide helps visitors self-select which eyebrow look they’re looking for. This helps visitors feel like they’re in control of the purchase process. Visitors set the pace at which they move from the research phase to purchase phase. Great reminder that content doesn’t always need to be text-based; providing high-quality interactive images is appropriate for a buyer that cares about appearances.
Based on the “Makeup 101” videos that Benefit produces, we assume that people who are beginning their journey into the beauty world are the target audience. As previously mentioned, the visuals that beginners spend time on shape our segment, campaign, trigger event, and notification plan. Here’s how I would increase the odds of converting first-time visitors who may be new to the makeup game:
- It’s data time! First-time visitors lack confidence to make a purchase or even consistently engage with free tutorials. We use Visitor Journey Analytics to identify typical funnel drop-offs for a first-time visitor and collect information on what content they consumed prior to that point.
- Create a special place for those visitors — segment them. For this segment, we are focusing on first-time or returning visitors who haven’t made a purchase or added products to the cart, but consumed a certain amount of “Basics” videos and read reviews on at least 3 products.
- Keep Campaigning. Now, a trigger event may be the absence of it. In our case, when videos and products are reviewed, but nothing is added to cart, we know it’s our time to shine and send a notification. Many outcomes are possible for this campaign. Let’s focus on leading a new visitor to “Explore Brow Transformation Guide”. We lead them to see what they may expect from the product.
Why this notification at this time?
- The visitor was qualified for a segment by watching at least 3 videos on brow basics and reading at least 3 product reviews — yes, it’s that specific.
- The platform predicted that visitor may not be finding their perfect product and would likely bounce. To lower bounce rate, a link to a visual guide appears — this is engagement.
First-time visitors may be hesitant to purchase, even after watching some how-to videos or plowing through a few product reviews. These notifications promote engagement and we know (through visitor journey analytics) that engagement of this sort is a precursor to revenue. More on visitor journey analytics in a future post!
Identity is core to marketing. An ability to collect and understand a visitor’s browsing patterns is a prerequisite to make predictions about their future behavior. It enables you to know the customer more intimately, and to anticipate their needs. Intempt is a product designed to help every company be smarter with their consumers. Given our investment in big data, predictive modeling and notification based marketing, and high-touch customer service, we are uniquely committed to deliver AI that transforms the customer experience.