The insurance sector benefits greatly from n=1 personalization (aka. hyper-personalization, aka. Segment of One). One company we work in that market segment was faced with a lack of coordination in messaging across channels, as well as stagnant or declining renewal rates. The question was whether more relevant and better coordinated messaging might make a difference in renewals, so we agreed to test that. For this purpose, we implemented highly-personalized communications, optimized by channel and message frequency at the individual customer level, plus AI-enabled renewal workflows that leveraged predictive renewal risk scores and other indicators. The result was a statistically-significant 60 […]

Apparel retail presents an excellent example of the problems and opportunities for n=1 personalization. A key problem for apparel retailers is that products change every season, so it’s especially difficult for legacy systems to make smart suggestions, due to sparse data, especially at the start of each new season. Another problem is: Let’s say a male visitor bought only one item so far (a blue shirt). This doesn’t mean that’s all he’s interested in is blue shirts. (Practically every man in every apparel database owns at least one blue shirt.) So in effect, you still know practically nothing about that […]

Mutual funds and asset management are a great use case for n=1 personalization (aka. hyper-personalization, aka. Segment of One). A leading technology that enables this is SOLUS.ai which was a first mover, and is currently a market leader in the AI-First category of customer engagement software. SOLUS acts as a system of intelligence that sits between users’ existing data sources and their existing engagement channels, generating individual customer-level nudges that combine recommendations, propensity scores and stacked models, rather than broad segments or static rules. One retail brokerage firm that uses SOLUS achieved a 27% increase in open rate and a […]

Consumer durables is a domain that offers especially rich rewards from n=1 personalization (aka. hyper-personalization, aka. Segment of One). Here’s an example. . . A top audio equipment brand we work with has a strong commitment to hyper-personalization across channels. As a result of those efforts, they reported an 81% increase in e-commerce sales and a 35% increase revenue from AI-driven targeting, in addition to significant improvements in CRM outcomes, related to CDP-powered journeys. A top consumer-electronics brand we work with has been able to personalize discovery across its store, its search function, and its recommendations (“You Might Also Like”), […]

The food and beverage industry offers very high-impact opportunities for n=1 personalization (aka. hyper-personalization, aka. Segment of One). One restaurant brand we worked with uses our technology to show context-aware recommended items, based on time of day, foot traffic and menu-item popularity. This resulted in 6-20% incremental average order size, depending on the geographic location. (All incremental results were quantified vs. control groups.) Another brand achieved more than a 10% increase in average order size and 2.8x higher conversion rates as compared to previous targeting methods. Another program achieved more than a 40% click-through rate, leading to more than a […]

Grocery retail is an excellent use case for n=1 personalization (aka. hyper-personalization, aka. Segment of One). One omnichannel grocer we work with has more than 125 stores spread across 35 cities. They asked us to create a single customer view, and to implement n=1 messaging for better orchestration across app, web, SMS and email. Their case illustrates the performance boost that’s still on the table for many grocery and dry goods brands, even after implementing technology that includes a loyalty program, an app, email and SMS, as well as initial segment-led marketing efforts (including RFM cohorts), as well as various […]

Personalization in travel and hospitality is very complex because it has to capture and anticipate human intent across multiple channels, touchpoints, and contexts, including browsing, booking, check-in, on-property experience, and post-stay re-engagement. Guests interact across websites, online travel agencies, mobile apps, loyalty programs, call centers, and on-property — often on systems that don’t share identifiers. Therefore, stitching together a coherent 360 view can be quite challenging. Often, the result is inconsistent personalization across channels. For example, a guest who booked via Expedia might receive a generic email offer from the hotel that’s not in synch with details of their booking […]