Strategies for Effective Customer Journey Optimization

Surveys can serve an important purpose. We should use them to fill holes in our understanding of the customer experience or build better models with the customer data we have. As surveys tell you what customers explicitly choose to share, you should not be using them to measure the experience. Surveys are also inherently reactive, surface level, and increasingly ignored by customers who are overwhelmed by feedback requests. This is fact. There’s a different way. Some CX leaders understand that the most critical insights come from sources customers don’t even realize they’re providing from the “exhaust” of every day life with your brand. Real-time digital behavior, social listening, conversational analytics, and predictive modeling deliver insights that surveys alone never will. Voice and sentiment analytics, for example, go beyond simply reading customer comments. They reveal how customers genuinely feel by analyzing tone, frustration, or intent embedded within interactions. Behavioral analytics, meanwhile, uncover friction points by tracking real customer actions across websites or apps, highlighting issues users might never explicitly complain about. Predictive analytics are also becoming essential for modern CX strategies. They anticipate customer needs, allowing businesses to proactively address potential churn, rather than merely reacting after the fact. The capability can also help you maximize revenue in the experiences you are delivering (a use case not discussed often enough). The most forward-looking CX teams today are blending traditional feedback with these deeper, proactive techniques, creating a comprehensive view of their customers. If you’re just beginning to move beyond a survey-only approach, prioritizing these more advanced methods will help ensure your insights are not only deeper but actionable in real time. Surveys aren’t dead (much to my chagrin), but relying solely on them means leaving crucial insights behind. While many enterprises have moved beyond surveys, the majority are still overly reliant on them. And when you get to mid-market or small businesses? The survey slapping gets exponentially worse. Now is the time to start looking beyond the questionnaire and your Likert scales. The email survey is slowly becoming digital dust. And the capabilities to get you there are readily available. How are you evolving your customer listening strategy beyond traditional surveys? #customerexperience #cxstrategy #customerinsights #surveys

Friday honesty: Customer-centricity is a lot harder to maintain than it seems. Even for those of us in Customer Success. The tendency is always to drift toward making our processes and focus company-centric rather than customer-centric. Don't believe me? Just look at one example of this: Customer Journeys. Many teams say that they have a defined Customer Journey. But rather than actually being oriented around the customer, for many the journey map is a list of activities from the company's perspective that are built around milestones the company cares about (contract signature, go-live, renewal, etc). I know about this, because I've been guilty of it in the past myself. I confuse my activity list with a customer journey and wonder why customers aren't as successful as they'd like. While important, that isn't a customer journey. It's an activity list. It's a rut none of us mean to fall into, but it's the natural drift because we live and breathe our own organization. So what do you do about it? How can you adopt a more customer-centric mindset in this area? TRY THIS APPROACH INSTEAD: 1. List out the stages your customers' business goes through at each phase of their experience with your product. Use these to categorize journey stage, rather than your contract lifecycle. 2. For each stage, list out what their experiences, expectations, and activities should be to get the results they want. Don't focus on listing what YOU do, but rather focus on listing what a customer does at each phase of their business with your product. List out the challenges they'd face, the business benefits they'd experience, the change management they'd have to go through, the usage they'd expect. Think bigger than your product here. 3. Then map what support a customer would need to actually accomplish these desired outcomes at each stage of the journey. Think education, change management enablement, training, etc. 4. Based on all of the above, you're finally ready to start identifying what your teams do to support the customer. ____________________________________________ Following a process like this helps build customer-centricity in 3 ways: 1. It causes customers to be the center of how you decide which activities are most important to focus on. 2. It empowers your team to become prescriptive about what customers should be doing for THEIR success. 3. It exposes what you don't know about your customers' business. And if you don't know something, just ask them. Don't make assumptions when you can instead talk to your customers directly. Avoid the company-centric drift, fight to maintain true customer-centricity however you can. This isn't just a nice to have in 2024. It's a business imperative that's important for any business to survive in this climate. But I want to hear from you! How do you guard your org from drifting to company-centricity? #SaaS #CustomerSuccess #Leadership #CustomerCentric

People overcomplicate growth strategy. Listen, if you're below $1,000,000 a year: Avoid: - Testing 10 new ads per week - Tweaking sales script every call - Changing your landing page monthly Instead: - Clearly map your customer journey - Start collecting data on every step - Research industry 𝗯𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸𝘀 - Spot your biggest bottleneck - Fix it, then do a new one Focus on this until you get big enough so you have specific teams and departments. Here's how you can do it: 𝟭/ 𝗠𝗮𝗽 𝘆𝗼𝘂𝗿 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗷𝗼𝘂𝗿𝗻𝗲𝘆 ↳ List all major steps people take from their first interaction with your business. 💡 Pro tip: Add steps after the sale, like activation, retention, referrals, etc. 𝟮/ 𝗦𝘁𝗮𝗿𝘁 𝗰𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝗻𝗴 𝗱𝗮𝘁𝗮 𝗼𝗻 𝗲𝘃𝗲𝗿𝘆 𝘀𝘁𝗲𝗽 ↳ Gather all metrics in a simple Google Sheet this will help you understand what's up. 💡 Pro tip: alongside conversion rates, track the time it takes to pass each stage. 𝟯/ 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗶𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗯𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸𝘀 ↳ Ask chat GPT, talk to people, spy on competitors, read industry reports, listen to podcasts... Find the data! You need to know what's considered a good CTR, good contact rate, good close rate in your space, for businesses of similar size and services. 𝟰/ 𝗦𝗽𝗼𝘁 𝘆𝗼𝘂𝗿 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗯𝗼𝘁𝘁𝗹𝗲𝗻𝗲𝗰𝗸 ↳ Compare the success of your user journey with industry 𝗯𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸𝘀. Find the most lagging. 💁♂️ Example: Your contact rate is 40%, the industry average is 60% while your close rate is 10%, the industry average is 30%. Your contact rate is 1.5 times smaller than 'average.' Your close rate is 3 times smaller than the 'average.' Rank all your bottlenecks like that and work on what sucks the most. 💡 Pro tip: sometimes your close rate is bad because you don't qualify prospects enough. Keep in mind that each stage affects the next one. 𝟱/ 𝗙𝗶𝘅 𝗶𝘁, 𝗼𝗻𝗲 𝗮𝘁 𝗮 𝘁𝗶𝗺𝗲 ↳ Now, when you lined up your bottlenecks, analyzed probable causes, and picked one to fix. Dive into tactics if you don't know how to do it. 💁♂️ Example: You figured that your close rate sucks, so this is your target to solve. Why tho? • Google how to increase close rate • Read a chapter from a book • Watch a YouTube video 1. Close the knowledge gap. 2. Come up with the hypothesis. 3. Implement the change and watch. Worked? — Great. ↳ Move to the next problem to solve. Didn't? — Great. ↳ Lesson learned. Try another way. This is about as complex as it should be before $1M. Good luck! P.S. Do you use benchmarks in your strategy? ♻️ Repost if this was helpful. ➕ Follow Lian for more like this.

Numbers tell you what happened. They never tell you why. This is the biggest blind spot in digital optimization today. Your analytics show where users abandon your digital experience. But the real reason they leave is almost never what your data suggests. Your bounce rate shows people leaving your product page, but it doesn't reveal the confusion they felt when comparing options. Your funnel analysis identifies drop-offs but misses the anxiety triggered when your shipping information appeared after they entered payment details. After optimizing digital experiences for companies like Adobe and Nike for over 16 years, I've seen this disconnect repeatedly. It occurs because of two powerful psychological forces: 1️⃣ Confirmation bias leads your team to interpret data in ways that confirm existing beliefs. "Customers want more features" becomes the lens through which all behavior is filtered. 2️⃣ The availability heuristic causes users to make decisions based on information that's readily accessible... not necessarily what's most important. I witnessed this firsthand with a client who spent months optimizing their product pages based on heatmaps and click data. Conversions barely moved. When we finally conducted qualitative research, we discovered users weren't leaving because they disliked the product... they simply couldn't tell which of the seven (!) options was right for their specific need. The solution wasn't in the quantitative data. It was in understanding the psychological barriers their analytics couldn't capture. The most powerful optimization approach combines: ↳ Analytics to identify WHAT is happening ↳ User research to understand WHY it's happening ↳ Psychological principles to determine HOW to fix it Are you listening to what your data is saying... or what it's hiding?

Grateful to be featured in the "Shoptalk Hot Takes" interview by Blenheim Chalcot and ClickZ.com alongside George Looker to unpack omnichannel commerce. 5 key takeaways and tactics from my conversation: 1. Design for Customer Continuity, Not Just Channel Expansion 💡 71% of customers expect brands to personalize interactions across every touchpoint. Tactical: Map out customer journey across channels, then design experiences that recognize and reward continuity—cart persistence, loyalty rewards, browsing history sync, etc. 2. Build the Infrastructure: Unify Data Streams Across All Touchpoints 🧠 Data fragmentation = missed opportunity Tactical: Integrate POS, e-commerce, mobile, social, and marketplace data into a centralized data lake or unified commerce platform. 3. Establish a Single Source of Truth for Customer Profiles 🔍 Brands with unified profiles see up to 2x better campaign performance. Tactical: Implement Customer Data Platforms (CDPs) to consolidate behavioral, transactional, and engagement data into unified customer profiles. 4. Partner Strategically for Scale, Not Just Stack ⚙️ A bloated tech stack doesn’t equal agility As I noted, Retailers are getting sharper about which partners can scale with them. Ecosystem efficiency matters more than ever. Tactical Step: Audit your tech stack and partnerships consistently. Prioritize partners that offer extensibility, future-proofing, and proven omnichannel success. 5. Measure What Matters: Unified KPIs Across Commerce 📈 You can’t optimize what you don’t measure holistically Tactical: Align your analytics stack to report holistically across channels—tie marketing to merchandising, CX to LTV, and inventory to revenue. 🧠 Bottom line: think holistically, move strategically, and build ecosystems that scale experience with agility, not just transactions. Complete list in comment 👇 #ecommerce #omnichannel #unifiedcommerce