Customer Loyalty Metrics

One of the biggest mistakes in growth is confusing “people use it” with “people love it.” So at Lovable, we built a composite qualitative metric to measure actual product love. The Lovable Score is a combination of: Net Promoter Score | NPS -> How likely are you to recommend? Sean Ellis PMF -> How would you feel if you could no longer use us? CSAT -> How satisfied are you? CES -> How easy was it to use? Any one of these on its own is usually too flawed, too narrow, or too easy to misread. But together, they start to tell a much more useful story. Our Lovable score has the following formula and weights: 35% NPS + 25% PMF + 20% CSAT + 20% CES Your mix might be different. But I’d really push every team to define what “love” actually means for their product, then measure it. Wrote more about how we built it here: https://lnkd.in/emQr6TFS And big shout out to Passionfroot, my awesome blog sponsor this week, who you should work with to scale your creator-led growth! #growth #lovable

Loyalty is failing. Gen Z & long-term commitment. 22% of Gen Z consumers consider themselves loyal to one brand is a clear warning for legacy loyalty strategies. Unlike previous generations, Gen Z doesn’t see brand loyalty as a long-term commitment, they’re loyal to moments, not just names. +43% increase in engagement and sales conversions among Gen Z Beauty brands offering "limited-edition drops" and collaborative experiences. +71% Gen Z say they would rather spend money on an experience than a product. >>Loyalty is FAILING, but why<< +Transactional systems feel outdated: Point-based rewards for repeat purchases don’t excite this audience. They expect more than discounts or free samples. +They’re brand-agnostic but experience-driven: Gen Z freely switches between brands if the experience, aesthetic, or values feel fresher or more aligned with their identity. +They buy into stories, not just products: They want to align with brands that represent something, social causes, cultural movements, or communities they relate to. >>DYNAMIC LOYALTY<< What’s this? as it name indicates its a system that rewards interaction, aligns with their values, and constantly evolves. And that is what your brand needs. → Create experience-driven loyalty programs: Offer early access to limited drops, invite-only events, or backstage content. Think like a fan club, not a punch card. +Example: A loyalty tier that unlocks tickets to a pop-up experience or an exclusive AR filter. →Let them co-create: Invite Gen Z customers to co-develop product ideas, designs, or campaign themes. Give them ownership in your brand’s creative journey. +Example: Voting on packaging designs or joining beta tester groups. →Align with their values: Sustainability, inclusivity, and social good aren’t nice-to-haves. they’re expectations. Use loyalty programs to reward actions too, like recycling, sharing causes, or supporting small creators. +Example: “Earn loyalty points by returning empties or attending a sustainability workshop.” →Deliver constant novelty: Rotate limited editions regularly. Use scarcity and surprise to create FOMO and buzz. +Gen Z doesn’t commit to a single brand, but they’ll keep returning if each visit feels fresh and share-worthy. →Go omnichannel but social-first. Should live across TikTok, Instagram, pop-ups, and web. Let them earn or unlock rewards through social engagement, not just purchases. +Example: A user gets exclusive content or perks for creating UGC with your brand. Bottom Line. Loyalty must be earned over and over through experience, relevance, and emotional connection. Think dynamic loyalty: a system that rewards interaction and go for it. Find my curated search of examples and get ready for your next HIT. Featured Brands: Balmain Benefit Chanel Charlotte tilbury Cerave Fennty L’Oreal OGX YSL #beautypackaging #beautybusiness #beautyprofessionals #experienceretail #luxuryexperiences #genz

Over the last year, I’ve seen many people fall into the same trap: They launch an AI-powered agent (chatbot, assistant, support tool, etc.)… But only track surface-level KPIs — like response time or number of users. That’s not enough. To create AI systems that actually deliver value, we need 𝗵𝗼𝗹𝗶𝘀𝘁𝗶𝗰, 𝗵𝘂𝗺𝗮𝗻-𝗰𝗲𝗻𝘁𝗿𝗶𝗰 𝗺𝗲𝘁𝗿𝗶𝗰𝘀 that reflect: • User trust • Task success • Business impact • Experience quality    This infographic highlights 15 𝘦𝘴𝘴𝘦𝘯𝘵𝘪𝘢𝘭 dimensions to consider: ↳ 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗲 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆 — Are your AI answers actually useful and correct? ↳ 𝗧𝗮𝘀𝗸 𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗶𝗼𝗻 𝗥𝗮𝘁𝗲 — Can the agent complete full workflows, not just answer trivia? ↳ 𝗟𝗮𝘁𝗲𝗻𝗰𝘆 — Response speed still matters, especially in production. ↳ 𝗨𝘀𝗲𝗿 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 — How often are users returning or interacting meaningfully? ↳ 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗥𝗮𝘁𝗲 — Did the user achieve their goal? This is your north star. ↳ 𝗘𝗿𝗿𝗼𝗿 𝗥𝗮𝘁𝗲 — Irrelevant or wrong responses? That’s friction. ↳ 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗗𝘂𝗿𝗮𝘁𝗶𝗼𝗻 — Longer isn’t always better — it depends on the goal. ↳ 𝗨𝘀𝗲𝗿 𝗥𝗲𝘁𝗲𝗻𝘁𝗶𝗼𝗻 — Are users coming back 𝘢𝘧𝘵𝘦𝘳 the first experience? ↳ 𝗖𝗼𝘀𝘁 𝗽𝗲𝗿 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻 — Especially critical at scale. Budget-wise agents win. ↳ 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻 𝗗𝗲𝗽𝘁𝗵 — Can the agent handle follow-ups and multi-turn dialogue? ↳ 𝗨𝘀𝗲𝗿 𝗦𝗮𝘁𝗶𝘀𝗳𝗮𝗰𝘁𝗶𝗼𝗻 𝗦𝗰𝗼𝗿𝗲 — Feedback from actual users is gold. ↳ 𝗖𝗼𝗻𝘁𝗲𝘅𝘁𝘂𝗮𝗹 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 — Can your AI 𝘳𝘦𝘮𝘦𝘮𝘣𝘦𝘳 𝘢𝘯𝘥 𝘳𝘦𝘧𝘦𝘳 to earlier inputs? ↳ 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆 — Can it handle volume 𝘸𝘪𝘵𝘩𝘰𝘶𝘵 degrading performance? ↳ 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 — This is key for RAG-based agents. ↳ 𝗔𝗱𝗮𝗽𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗦𝗰𝗼𝗿𝗲 — Is your AI learning and improving over time? If you're building or managing AI agents — bookmark this. Whether it's a support bot, GenAI assistant, or a multi-agent system — these are the metrics that will shape real-world success. 𝗗𝗶𝗱 𝗜 𝗺𝗶𝘀𝘀 𝗮𝗻𝘆 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗼𝗻𝗲𝘀 𝘆𝗼𝘂 𝘂𝘀𝗲 𝗶𝗻 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀? Let’s make this list even stronger — drop your thoughts 👇

Killer graph. Out of the £130 billion online non-food purchases we make in the UK, £27 billion of them get sent back to retailers. Our research with ZigZag Global shines a spotlight on the significant challenge online returns cause in the industry, focusing on those consumers who consistently and intentionally over-order - the "serial returners". Key stats ➡️ Around 11% of online shoppers are serial returners (frequently over-ordering with the intention of returning many items) ➡️They account for 24% of all online returns ➡️Serial returners send back, on average, £1,400 worth of online orders per year, compared with an average of £650. ➡️ This amounts to £6.6 billion of returns. ➡️ Almost three-quarters of serial returners are under the age of 45, and they return more than 42% of all their orders. A 1/4 of serial returners admit to over-ordering just to reach a minimum order value (often to trigger free delivery) only to return goods they had no intention of keeping. The same proportion also said they had returned items after finding them cheaper elsewhere or on promotions. While 18% admitted to returning items having already used them for a short period. There is no silver bullet here that is going to fix this issue for retailers. A nuanced understanding of specific triggers and barriers is essential to effectively target returners through pricing and returns options. 💥 For many boardrooms debating whether they should charge for returns, my thoughts are: 💥 The returns equation transcends simple binary choices between free or paid. Retailers must architect differentiated returns propositions that align commercial realities with customer lifetime value. Smart retailers will segment their returns strategy by customer profitability metrics, leveraging AI to identify purchase patterns that predict long-term value. This enables dynamic returns pricing that protects margins while fostering relationships with truly valuable customers. The goal isn't to punish returns – it's to price them according to their true cost to serve, while rewarding profitable shopping behaviours. There's also a paradox at play where customer acquisition costs are optimised but customer profitability is compromised. Many retailers are essentially subsidising unsustainable shopping behaviours at the expense of margin, unknowingly targeting customers they could do without. The real opportunity lies in leveraging returns data as a predictive indicator of customer profitability. By applying advanced analytics to returns patterns, seasonal purchasing behaviours, and cross-category browsing and mining deep behaviour insights, retailers can enable proactive intervention before profitability erodes. This shifts the conversation from universal policies to personalised solutions that can turn returns from a pure cost centre into a strategic lever for customer engagement and loyalty. Full research is available to download here ⬇️ https://lnkd.in/e5paRNWC

Have written about it in the past too, but strength of a brand cannot be measured by vanity metrics like number of award winning commercials, social media engagement/following or what other marketers think about the brand Here are 5 hard measurable business/marketing metrics which will tell you how strong your brand is 1. Price Elasticity of Demand: This is the measurement of change in demand with respect to the Price Elasticity= Percentage Change in Demand/Percentage Change in Price If you have a strong brand, you will have a lower price elasticity. Ideally as brand strength grows, the price elasticity should keep reducing 2. Contribution of Discounted Sales: Every brand has a standard market operating price( which could be MRP in few categories). And brands also have some sales through consumer discounts which are over and above the MOP Discounted Sales Contribution= Sales Volume with Discounts/ Total Sales Volume If you have a strong brand, the contribution of discounted sales will be lower. The ability to have more sales at the market operating price is a sign of a strong brand 3. Performance Ads Driven Sales: Every brand will have some organic sales( brand searches, repeats, Marketplace SEO etc) and some paid sales( Amazon ads, Google/FB ads) Performance Ads Driven Sales Percentage= Sales due to ads/Total Sales If you have a strong brand, the contribution of ads driven sales will be lower. A strong brand has higher repeats, higher brand searches and rank organically on top for generic searches on marketplaces 4. Performance Ads Driven Visitors: On the D2C website as well as marketplace listings, brands get both organic( brand searches and SEO) and paid ( Amazon Ads, Google/FB ads) visitors While the previous metric of ads driven sales is difficult for overall attribution( people clicking on ads to come to D2C website buys organically from marketplace is common), this is a easier metric to calculate Percentage of Performance Ads Driven Visitors= (Ads driven visitors on Marketplaces+ Ads driven visitors on D2C)/ (Total Visitors on Marketplaces+ Total Visitors on D2C) As brand strength grows, percentage of ads driven visitors should keep reducing 5. Share of Spends/Market Share: Share of spends in a category is the marketing spends done by the brand as a percentage of spends done by the entire category in a year. If a brand has a higher market share than share of spends, it means 2 things - Higher Conversion Rates & More Efficient Marketing Engine - High Baseline Sales When brands start, they would most likely have higher SOS than market share( as baseline is 0). But as brand strength grows, this number should be lower Strong brands should result in strong businesses. Done right, Investment in Brand Building always pay off financially. It means stronger brands are less reliant on performance marketing, discounts and can increase prices without drop in volumes.

Jessica just got promoted. She’s no longer our contact. We lost a $120K account because of that one promotion. It still hurts and it’s the reason we now measure something I call the 'Champion Dependency Score.' Jessica was our champion on a $120K account. She knew our platform inside out, trained her team, fought for us at renewal. For 18 months, every conversation went through her. She fixed every problem and handled every renewal question. Her replacement? Had never even heard of us. Then came the email that made it worse: “Hi Kelly, I’m taking over for Jessica. Can you send me some information about what you do for us? Also, we’re reviewing all our software spend this quarter.” That’s when it hit me: we didn’t have a customer relationship. We had a Jessica relationship. The panic audit I did that night: Single Point of Failure Analysis for Jessica's account: - Who introduced us to the company? (Jessica: Yes) - Who runs internal training? (Jessica: Yes) - Who handles our invoices/renewals? (Jessica: Yes) - Who do we text when there's an issue? (Jessica: Yes) - Who attends our quarterly business reviews? (Jessica: Yes) Score: 5/5 = 100% dependency. We were in trouble. I checked the rest of our portfolio. Out of our top 20 accounts, 14 had scores over 70%. That’s $1.8M ARR hanging by a single person in each account. Three months later, Jessica’s replacement churned us. Despite our best efforts, they went with a “simpler” solution. Translation: no one left inside could explain why we mattered. That loss forced us to create the Champion Dependency Score: - 0–20% → We can survive a departure - 21–50% → Some risk, manageable - 51–80% → High risk — widen relationships now - 81–100% → Crisis mode — one change away from churn What we do differently now: - Every meeting: 2+ customer attendees - Map contacts in IT, Finance, End Users, Leadership - QBRs include the champion’s boss - Track “relationship breadth” as part of our health score The hardest lesson: The stronger your champion feels, the more dangerous it is. Jessica loved us so much she kept it all on her plate and when she left, so did our value. Now I ask my CSMs: If your main contact vanished tomorrow, who else would fight to keep us? If the answer is “no one,” you’re not managing a customer. You’re managing a single point of failure. Who’s lived through their own “Jessica moment”?

I recently mentored a new Head of HR at a 1,200-person tech company to build her first People Ops dashboard. Not a PowerPoint. Not a vibes report. A real dashboard that said: “I know how this company makes money, and how my team helps it grow.” First, we clarified her goals: ✅ Understand what drives revenue and retention ✅ Make people strategy a lever for innovation, not just operations ✅ Reset how HRBPs see themselves - from support function to business collaborator Her exact words: “I want to build the muscle to operate like any other exec on the team, while teaching my team to embrace a ‘biz-first’ mindset.” Then we built a dashboard to match. 📈 Revenue per Employee 💡 Why: Shows workforce productivity + ROI on talent 🎯 Target: $250K+ (varies by industry); improve quarter-over-quarter Tip: Segment by GTM, R&D, G&A to spot optimization opportunities 📈 Profitability per Employee 💡 Why: Growth is great. Profit funds the future. 🎯 Target: $50K–$150K per employee (varies by stage/directionally, aim up). Tip: Segment by function or team to see who’s building vs. burning value. 📉 Voluntary Attrition (Regrettable + Non) 💡 Why: Attrition is culture + leadership feedback in disguise 🎯 Target: Regrettable <7% annually Tip: Cut by: Team, tenure, manager to reveal hotspots 🌟 Top Talent Retention 💡 Why: Losing high performers = losing velocity 🎯 Target: >90% annual retention of top 10–15% Tip: Track: Internal mobility + development investments 💬 Employee Engagement (eNPS + Pulse) 💡 Why: Engagement predicts performance, CX, and attrition 🎯 Target: eNPS >30; Pulse up trending Tip: Segment: Trust, DEI, belonging, confidence in leadership 🧑💼 Manager Effectiveness Index 💡 Why: People don’t quit companies, they quit managers 🎯 Target: 85%+ favorable across feedback, clarity, support Tip: Sources: Pulse, 360s, retention by manager 🎯 Goal Alignment Rate 💡 Why: Strategy without execution = wasted time 🎯 Target: 95% with 3-5 measurable goals aligned to OKRs Tip: View: By team and level 🚀 Time to Productivity (New Hires) 💡 Why: Faster ramp = faster ROI 🎯 Target: <60 days to first impact deliverable Tip: Benchmarks: Sales ramp, engineer first ship, CSAT lift 🪜 Leadership Bench Strength 💡 Why: You can’t scale what you haven’t built for 🎯 Target: 75% of key roles with 2+ ready successors Tip: Cut by: Function, level, diversity 💵 Compensation Equity + Transparency 💡 Why: Trust starts with fairness 🎯 Target: 100% pay equity audits + 100% manager training in comp philosophy Tip: Overlay: Gender, race, tenure, role 🔧 People Ops Health Score 💡 Why: Broken processes break trust 🎯 Target: <5 days to close HR tickets, 80%+ system adoption, 90%+ hiring manager satisfaction Tip: Layer in: “Do internal systems help or hinder your work?” Now she, nor her HRBPs are waiting to be brought in. They’re co-pilots at the table, with the data to match. Because great HR doesn’t just build culture, it builds companies.

Amit dedicated 7 years to his company. He started at ₹12 LPA and, after years of hard work, reached ₹20 LPA. One day, he casually asked a new hire about their salary—₹30 LPA. Shock. Betrayal. He had trained others, handled crises, and never dropped the ball. Yet, a newcomer with less experience made ₹10 lakh more. His manager’s response? "We value you, but external hires are paid market rates." Reality check: New hires get market pay. Loyal employees get small increments. Appreciation ≠ Compensation. Amit tested the market and got a 40% hike in 90 days. Suddenly, his company wanted to match it—but he had already moved on. Lesson? Loyalty should be a two-way street. Know your worth. Keep an eye on market trends. Negotiate what you deserve. Because staying too long without evaluating your worth is the costliest mistake.

If Indian retail wants to win, it must shift its focus from discounts to this, Recently, in a conversation about retail strategy, someone asked me, “Why do so many brands struggle to build long-term loyalty?” The answer is simple: They’re addicted to discounts. Price cuts create a temporary spike in sales. But what happens when the sale ends? Customers move on to the next discount. There’s no loyalty in a race to the bottom. If a brand’s only value proposition is being the cheapest, it’s not a brand, it’s a commodity. And commodities don’t build relationships. The strongest retail brands win on something deeper: ✅ Product innovation: If your product isn’t unique, no discount can save you. UNIQLO doesn’t rely on markdowns, it invests in technology-driven fabrics like HeatTech and AIRism, making its products essential rather than seasonal. ✅ Customer Experience: Shopping isn’t just about the product, it’s also about how customers feel. IKEA built an entire ecosystem around its stores, cafes, play areas, interactive showrooms, turning shopping into an experience people return for, even when they don’t “need” anything. ✅ Community Building: The most powerful brands don’t have customers, they have believers. Starbucks doesn’t just sell coffee; it sells familiarity and personalisation. People go there for the experience of “their” drink, their name on a cup, their place to work or meet. That’s not a transaction, it’s a relationship. + The brands that rely on discounts are playing defense.  + The brands that invest in differentiation are playing to win. So the real question isn’t how much you can lower your price; it's how much value you can create. #retailleadership #beyonddiscounts #brandbuilding

One of the biggest takeaways I spotted from Intuit Mailchimp’s analysis of the 2024 holiday shopping season is that the new year is ripe with new opportunities to drive loyalty. Here’s why → 64% of orders from Mailchimp customers with connected stores came from new customers during Cyber Weekend 2024. That's a huge opportunity to grow your loyal customer base! And research we produced with Canvas8 tells us that the best kept secret to driving loyalty is actually grounded in science. Our Loyalty Wheel reveals 4 key drivers of loyalty: 1. Reward: Our brains love rewards. Create a sense of reciprocity by offering exclusive deals, personalized discounts, or early access to new products. 2. Memory: Make it easy for customers to remember (and repeat!) positive experiences with your brand. Design a frictionless customer journey, offer subscriptions for frequently purchased items, and send well-timed reminders. 3. Emotion: Foster an emotional connection that goes beyond transactional exchanges. Align your brand with causes your customers care about, share authentic stories, and build a sense of community. 4. Social Interaction: Encourage customers to share their love for your brand with friends and family. Create opportunities for user-generated content, run refer-a-friend programs, or host exclusive events. And here's how to put it all into action: 🎉 Surprise and delight: Gift your customers with unexpected rewards. And just not generic discounts. Offer exclusive experiences or partner with like-minded brands to create unique offers. 🛝 Streamline every touchpoint: Remove friction in the customer journey with automation. From browsing to purchasing to post-purchase support, make it easy and enjoyable to do business with your brand. 🎯 Prioritize personalization: Craft your messaging and build authentic connections. Use data and AI analysis to understand your customers' values and preferences and use those insights to create content that resonates. 🤗 Give VIP treatment: Make your customers feel like VIPs. Give them early access to new products, invite them to exclusive events, or feature them on your social media channels. Download Mailchimp and Canvas8’s The Science of Loyalty and The Strategic Loyalty Playbook for a deep dive into the science, complete with actionable strategies and inspiring examples: https://bit.ly/49FJayO Make 2025 the year of the loyal customer. You got this.