It is not enough to identify and categorize visitors according to standard demographic models; in order to increase conversions, merchants must target their messages so they align with a thorough understanding of the purpose and interest behind each visit. Good segmentation and targeting creates a dialogue between merchant and visitor that provides a mutual benefit, improves the shopping experience and makes conversions happen.
To do this, visitor engagement must be fully understood and then rendered into a form that is immediately actionable. Yet, merchants must have a means to confidently assert their in-depth knowledge of the association between their customers and their brand and/or product mix.
The digital environment provides a means for a much more constructive engagement between merchant and prospect, one that is driven by a much more by a tailored customer experience than by a one-size-fits-all, repetitive message.
Segmentation: Definition and Implementation
The meaning of segmentation is often mischaracterized as a catalogue of visitor types, which denotes a grouping based on more static attributes such as age, gender, location, device and social influence as measured by a score. A greater degree of segmentation tends toward personalization, where the goal is to characterize at the individual level, creating super-fine segmentation, resulting in many tiny buckets of audience which we now know increases the engagement challenge and drastically reduces ROI.
Segmentation should be dynamic. While we obviously care about the visitor, we also want to know what each visitor tells us about interest and intent. We must segment the experience not just visitor, and as such, we must address the demographic, behavioral and historical contexts of each visit.
What Really Improves the Visitor Experience?
Lost in the tumult of the rapid development of e-commerce and the improved costs, selection and convenience - which everybody wants - is a complete understanding of what actually improves the visitor experience at the personal level. Eventually, the marginal return on the three basic drivers of aggregated e-commerce will diminish. It is actually already happening. We believe that an engaged visitor experience that reflects individual behavior and context will become the key ingredient to improving CR and AOV.
The digital environment allows for a deeply interactive exchange of information between merchant and visitor. The enables a constructive dialogue between merchant and visitor, that should provide benefits for both parties.
For such a dialogue to take place, merchants need to think proactively about collecting data from each visitor. Each page view has a context that is meaningful in understanding what it will take to get the visitor to convert. Unfortunately, this context involves a vast array of data points such as the URL history of the session, page views per second, time since before and after add to cart, cart attributes, visit history and demographics. A significant challenge is how to organize all this data in such a way that is relevant and “actionable” from one page view to the next. Due to the large volume of data involved, this can be technically challenging and care must be taken not to impede overall site performance. In order to do this, we need to think about how we can store this data so that we can quickly derive the insights needed to provide clues to effective segmentation and targeting.
Things that we’re interested in include:
- Conversion funnel – How productive is your traffic?
- Waterfall characteristics - How visitors track through your site and where they fall off?
- Converter to non-converter profile comparisons – Who is converting? How much revenue? What are there common attributes and what groups of non-converters look like they should join the conversion cohort?
- Time in cart stats – At what point in time does a cart with a given value look like it may be abandoned?
- Visit count conversion stats – How does visit count affect conversion rate?
- Trends in revenue per visitor – How valuable is each visitor to your site?
All of this should be filterable and separately viewable according to the common static data carried by each visitor including location, device, browser, time of day and day of week. Since the sole purpose of this data is to suggest ways to engage visitors in order to increase CR and AOV, these same data points must be applied to the challenge of determining traffic segments and how to target these visitors.
Getting one’s mind around the meaning of all of this data and harnessing it to serve the purposes of both merchant and customer alike is a challenge. One can mistakenly conclude that the task of segmentation and targeting is not well suited to the overworked marketer. We have heard the erroneous claim that the demographics of digital commerce are so vast and product mixes are so varied, that these circumstances conspire to exceed ability of mere mortals to make sense of; and thus, unfortunately, the only rational answer is contained in the deliberately incomprehensible phrase “machine learning.”
Still, we cannot lose sight of the fact that the experience of the merchant is the foundation of their enterprise. As such, this experience is hugely valuable. Moreover, it must be brought to bear in such a way that the marketer fully understands the mechanics of how her expertise is applied. We do see that there is a sizeable opportunity for agencies and digital services to provide a platform with the data structure, rules capability and user interface that can demystify segmentation and targeting so that the merchant understands why things are happening and is confident that all is aligned with her business objectives.
We know the digital environment of e-commerce enables all sorts of productive engagement that when captured through the lens of segmentation and targeting can better serve the merchant and visitor in a measurable and accountable way. We can achieve far more objective understanding of how visitors engage and what want to find. Further, we can use this understanding to appeal to the specific purpose of each visit. The following are a few principles that lead to effective segmentation and targeting campaigns.
- Visibility: The campaign must be visible. The rules that define each segment, should group together cohorts of similar interest but not be so restrictive or “narrow” that no one qualifies in the segment. In order to generate redemptions the segments need to see traffic.
- Exclusivity: Visitors need to know that the targeted message or offer is directed to them. It is important that the offer effectively draws attention to itself and that the visitor is not distracted by peripheral messages that are more generic in nature.
- Responsive: Visitors need to make a connection between the offer and an action that they performed on the site. This could be as simple as a particular pageview, adding an item to cart or even just slowing down their pageview per minute rate. If they see that a targeted message or offer is obviously a response to their action it is more likely to get their attention.
- Improved Experience: Visitors need to feel that their actions are rewarded and that they have an increasing stake in the shopping activity as they get deeper into the site flow. A targeted offer should enhance the visitor’s experience by providing options that are exclusive to that visitor. For example, when two offers are collected with different minimum purchase thresholds, the visitor can chose the most advantageous offer that fits his or her budget. Yet there is no guarantee that those offers will be made on a subsequent visit.
- Facilitate Conversion: Finally, visitors must be encouraged to convert. The mechanics of receiving and redeeming a promotion must facilitate conversion and not inhibit it. Make targeted offers only when they are necessary and then get out of the way of the buying process.
Segmentation use cases help to clarify both the data tracking requirements as well an approach towards targeting. For instance, in the simplest case, often an early add-to-cart event can signal the purchase intent of a given visitor. Analysis of tracking data can tell when in terms of time on site, number of page views and value in cart if a given visitor is likely to purchase during this visit. It would then make sense, then, to exclude visitor traffic that is exhibits purchase from any additional incentives. This way offers are made only to those visitors who seem hesitant, potentially because they are browsing other sites or are particularly price sensitive. The following are examples of the types of traffic that can be isolated by segmentation rules and then targeted by relevant offers.
- Purchase intent: Understanding which visitors exhibit purchase intent and which ones do not – and then targeting those who do not.
- Upsell: Encouraging the visitor to increase cart size by offer larger incentives for higher minimum purchase thresholds.
- Push-to-close: Opposite of upsell, push-to-close detects if a cart is in danger of being abandoned and makes an offer that the current cart value already qualifies for.
- New customer: Detects if the shopper is a first time visitor or has visited previously but has not purchased, makes a one-time, aggressive offer to secure the conversion.
- Loyal customer: Detects if the shopper is a repeat purchaser and if prior accumulated purchasing amounts qualify for a loyalty while at the same time checks to see if prior accumulated discount amounts do not disqualify for the loyalty offer. The combination of new and loyal customer targeting is known to be effective as a long-term customer acquisition and retention strategy.
- Repeat Visitor: Within a 2-day period, we find that each site displays a standard conversion rate falloff. This follows a pattern wherein CR increases and plateaus for the first to the third or forth visits. At around this visit we begin to see a falloff in CR. It is as though, the visitor has decided to purchase elsewhere but they are confirming their decision with a final visit.
- Complimentary Product: Detects the presence of a given product or product category in cart and offers a discount on a complimentary product or product category.
- Specific interest: Allow the visitor to browse for specific period of time. If during this timeframe, the visitor views a list of url’s (pages) wherein a given character string or set of character strings can be found, make an offer that can be applied to the purchases of products on those pages.
- Content Heavy: High content sites allow visitor a lot of room to engage on site. The underlying theme of the content may relate to the available products, however, sometimes visitors lose sight of the fact they are actually browsing a store. Once a visitor is sufficiently engaged, having spent a lot of time and page views, they are often responsive to offers that remind them that the content they are viewing can be purchased and here is something to facilitate that purchase.
As segmentation and targeting is fundamentally data driven, it provides inherent accountability, offers verifiable support for merchant’s business objectives and gets smarter as its underlying data gets richer – and more “actionable.”
We expect this will increasingly become a competitive necessity for our customers and prospects. We believe that driving conversions is the tip of the spear in e-commerce. This is especially the case as the cost of traffic acquisition increases. Beyond the demonstrable ROI of segmentation and targeting campaign strategies, as the underlying platforms that support these solutions deepen their understanding of the merchant customer relationship, we believe all sorts of interesting new opportunities should start to emerge.
Are you interested in learning more about segmentation? Derek Adelman, Vice President of Operations for Fanplayr will guide our audience members through a process of segmentation and targeting to nail down the information behind any and all site visits. Sign up for the webinar which will take place on Tuesday, April 14 at 12 p.m. ET.