Email Segmentation: 39% Higher Opens, 38% More Conversions

Effective email segmentation is the difference between generic mass emails and personalized messages that drive real results. When you segment your email list properly, you can achieve open rates 14.31% higher and click-through rates 100.95% higher than non-segmented campaigns, while dramatically improving conversion rates and customer lifetime value. This comprehensive guide covers behavioral segmentation, demographic targeting, predictive analytics, and RFM analysis to help you send the right message to the right person at the right time—transforming email marketing from a cost center into your most profitable customer acquisition and retention channel.

Why Most Email Marketers Fail at Segmentation

Despite 77% of email marketing ROI coming from segmented, targeted, and triggered campaigns, 68% of marketers still send the same message to their entire list. This "batch and blast" approach wastes money and damages sender reputation, as subscribers receive irrelevant offers leading to 42% marking emails as spam, 35% unsubscribing immediately, and 78% simply ignoring future messages. The opportunity cost is enormous—businesses lose $500,000-2,000,000 annually in potential revenue from poor segmentation.

The false beliefs holding marketers back include thinking segmentation takes too much time (reality: Klaviyo automates 80-90% of segmentation), fearing smaller segments mean less revenue (reality: targeted emails to 500 engaged subscribers outperform generic emails to 10,000), believing demographics are enough (reality: behavior predicts purchases 5-8x better than age or gender), and assuming complex segmentation requires coding skills (reality: Klaviyo's visual builder makes it point-and-click simple).

The segmentation opportunity reveals that segmented campaigns generate 760% more revenue than non-segmented campaigns, targeted emails achieve 18x higher transaction rates, personalized CTAs convert 202% better than generic ones, and segmented email lists improve deliverability by 28-42% (fewer spam complaints, higher engagement signals sender quality to ISPs).

The Segmentation Framework That Drives Results

Effective segmentation combines four dimensions working together: Demographic segmentation (who they are: age, gender, location, job title, company size, income level), Behavioral segmentation (what they do: purchase history, browsing activity, email engagement, product preferences, site visits), Psychographic segmentation (why they buy: values and beliefs, lifestyle choices, pain points, motivations, buying triggers), and Lifecycle stage (where they are: prospects, first-time buyers, active customers, VIPs, at-risk, churned).

The segmentation pyramid builds sophistication over time: Level 1 - Basic Demographic (segment by location, age, or gender: 10-15% improvement vs no segmentation), Level 2 - Engagement-Based (separate engaged from unengaged subscribers: 30-45% improvement), Level 3 - Behavioral (segment by purchase history and browsing: 60-90% improvement), Level 4 - Predictive (use AI to predict future behavior: 100-150% improvement), and Level 5 - Dynamic Multi-Dimensional (combine all factors in real-time: 200-300% improvement).

Most businesses should aim for Level 3-4 within 90 days of implementing Klaviyo, as these levels deliver optimal ROI without excessive complexity. Level 5 is reserved for advanced users with large lists (50,000+ subscribers) and sophisticated marketing operations.

Demographic Segmentation: The Foundation

While demographics alone aren't enough, they provide essential context for other segmentation types. Geographic segmentation enables location-based offers (free shipping in specific regions, local event invitations, weather-triggered campaigns), international considerations (language preferences, currency, cultural holidays), timezone optimization (send emails when customers awaken, not 3am), and regional product availability (don't promote products unavailable in customer's area).

Example: Clothing retailer segments by climate zone—customers in Florida see summer apparel year-round while Minnesota customers receive winter gear promotions starting August. This increases relevance 45% and reduces returns from seasonal mismatches.

Age and gender segmentation works when products naturally segment by these factors: skincare brands adjust messaging by age group (anti-aging for 40+, acne solutions for teens), fashion retailers show gender-appropriate styles, toy companies target parents by child's age, and financial services customize based on life stage. However, avoid stereotyping—always allow customers to self-select preferences rather than assuming based on demographics alone.

Income and occupation targeting enables luxury brands to identify high-value prospects, B2B companies to segment by job title and seniority, educational institutions to target by degree level, and financial services to offer appropriate products by income bracket. Klaviyo enriches customer profiles with third-party data including estimated income, job title, and company information, enabling sophisticated targeting without directly asking sensitive questions.

Behavioral Segmentation: The Game-Changer

Behavioral data predicts future purchases 5-8x more accurately than demographics because past behavior is the best predictor of future behavior. Purchase history segmentation creates powerful segments: first-time buyers (need nurturing toward second purchase—critical retention point), repeat customers (upsell higher-tier products, introduce new categories), frequent buyers (VIP treatment, loyalty program, early access), and lapsed customers (win-back campaigns with compelling offers).

Calculate customer lifetime value (CLV) segments: High-CLV customers ($500+ lifetime spend) receive white-glove treatment, exclusive previews, personal shopping assistance, and premium customer service. Medium-CLV ($100-500) get standard loyalty benefits, occasional exclusive offers, and category-based recommendations. Low-CLV (under $100) receive nurture campaigns to increase engagement, education about product value, and activation-focused promotions.

Product category affinity reveals what customers care about most. E-commerce businesses segment by primary category purchased (bought dresses 3x → "dress lover" segment, purchased running shoes 2x → "runner" segment) and browsing behavior (viewed skincare 10+ times → interested in skincare). This enables hyper-relevant product recommendations increasing click-through rates 65-120% and dramatically improving conversion as customers see products they actually want.

Example: Beauty retailer with 15 product categories segments customers by top 2-3 category affinities. "Skincare Enthusiast" receives new serum launches, ingredient education, and skincare routines. "Makeup Artist" gets color cosmetics, application tutorials, and trend alerts. This increased email revenue per recipient from $0.88 to $3.45—292% improvement from showing relevant products.

Browsing behavior and engagement identifies high-intent prospects: product viewers who didn't purchase (browse abandonment flow targets 2-5% conversion), cart abandoners (highest intent—10-25% recovery rate with proper sequence), repeat visitors without purchase (curious but hesitant—need social proof and guarantees), and engaged email clickers (interested but not ready—nurture with education).

Email engagement segmentation separates subscribers by interaction level: Engaged subscribers (opens 40%+ of emails, clicks 15%+) receive maximum email frequency with early access offers, new product previews, and insider content. Moderately engaged (20-40% opens) get standard frequency with varied content types and A/B tested approaches. Low engagement (5-20% opens) need reduced frequency with only high-value offers and preference center options. Inactive subscribers (under 5% opens, or no opens in 90 days) enter sunset sequence—re-engagement attempt → preference update → final warning → removal from list (protects deliverability).

Example: E-commerce brand segments by 90-day engagement score. Highly engaged (15,000 subscribers) receive 8-10 emails monthly, achieving 38% open rate and $4.20 revenue per recipient. Low engaged (8,000 subscribers) receive 2-3 emails monthly, achieving 12% open rate but $2.80 revenue per recipient (higher quality opens). This strategic frequency prevents list fatigue while maximizing revenue from each segment.

RFM Segmentation: The Revenue Accelerator

RFM (Recency, Frequency, Monetary) analysis scores customers on three critical dimensions providing more actionable insights than any single metric. Recency scoring (0-5 scale): 5 = purchased within 7 days, 4 = 8-30 days ago, 3 = 31-60 days, 2 = 61-180 days, 1 = 181-365 days, 0 = over 365 days or never purchased. Recent customers are most likely to buy again—priority targeting for new offers.

Frequency scoring (0-5 scale): 5 = 10+ purchases, 4 = 6-9 purchases, 3 = 4-5 purchases, 2 = 2-3 purchases, 1 = 1 purchase, 0 = no purchases. Frequent buyers are brand-loyal—perfect for VIP programs and referral requests.

Monetary scoring (0-5 scale based on percentiles): 5 = top 10% of spenders, 4 = 70-90th percentile, 3 = 40-70th, 2 = 20-40th, 1 = 10-20th, 0 = bottom 10%. High spenders deserve premium treatment and exclusive offers.

Key RFM segments and strategies: Champions (RFM 4-5-5 to 5-5-5: recent, frequent, high spenders) receive VIP treatment with early access to sales and new products, exclusive products or limited editions, personal shopping or concierge service, referral program invitations (they'll bring quality customers), and thank you gifts or surprise bonuses. Champions generate 40-60% of revenue despite being only 5-10% of customers—invest heavily here.

Loyal Customers (RFM 3-5-3 to 4-5-4: frequent but lower recency or spend) get loyalty program perks and tier advancement, cross-sell campaigns to increase category breadth, appreciation messages with surprise discounts, and beta access to new features. Loyal customers are emotionally connected to brand—leverage this with community building and co-creation opportunities.

Big Spenders (RFM 3-2-5 to 5-2-5: high monetary but lower frequency) need upsell campaigns for even higher-tier products, exclusive luxury or premium offerings, frequency-building tactics (subscriptions, bundles), and white-glove customer service. Goal: increase purchase frequency to transform into Champions.

Promising Customers (RFM 4-2-2 to 5-2-3: recent buyers but low frequency/spend) receive onboarding series to increase product knowledge, cross-sell campaigns to expand category engagement, education about product value and benefits, and early-stage loyalty program enrollment. These customers show potential—invest in education and engagement to unlock future value.

At-Risk Customers (RFM 2-4-4 to 3-5-5: historically valuable but declining recency) get win-back campaigns with compelling offers, feedback surveys to identify problems, reminder of account value (points, history), and VIP re-engagement incentives. Saving at-risk customers is 5-7x cheaper than acquiring new ones—aggressive retention efforts pay off.

Need Attention (RFM 2-3-3 to 3-3-3: average on all dimensions, could go either way) receive targeted campaigns matching past interests, gentle frequency increases to test engagement, value-focused messaging highlighting benefits, and preference center invitations to optimize content. These customers are on the fence—small improvements in relevance can push them toward loyalty or disengagement.

Lost Customers (RFM 0-1-1 to 1-2-2: long-dormant, low historic value) need final win-back attempts with deep discounts, survey about why they left, option to update preferences rather than unsubscribe, and sunset policy (remove after 12 months dormant to protect sender reputation). Most won't return—prioritize higher-value segments.

Example: Home goods retailer implemented RFM segmentation on 45,000-person list creating 9 distinct segments. Champions (2,200 customers) received white-glove concierge service, exclusive previews, and VIP events—generating $840,000 annual revenue ($381 per customer). Lost customers (8,500 subscribers) received 1 email per quarter with aggressive discounts—generating $62,000 annual revenue ($7 per customer). Overall email revenue increased from $1.2M to $2.8M annually—133% improvement from strategic segmentation.

Predictive Segmentation: The Future is Now

Klaviyo's predictive analytics use machine learning to identify future behavior before it happens, enabling proactive marketing. Predicted customer lifetime value analyzes historical patterns to forecast which customers will become your most valuable, identifying high-CLV prospects within first 30 days (spend acquisition budget here), predicting which segments will drive long-term revenue, and allocating marketing resources to highest-value segments.

Example: Subscription box company uses predicted CLV to segment new subscribers. Top 20% of predicted CLV (customers likely to subscribe 12+ months) receive premium onboarding with bonus products ($25 cost), personal welcome calls from customer success team, and exclusive access to limited editions. This group achieves 78% 12-month retention vs 42% for low-predicted segment—the $25 onboarding investment returns $240 average annual revenue difference.

Churn risk prediction identifies customers likely to stop purchasing based on declining engagement patterns (opens dropping 60%+ over 30 days), extending purchase recency beyond normal cycle, reduced site visits and browsing, and negative sentiment from customer service interactions. Proactive retention triggers when churn score exceeds 70% with win-back email series featuring strong offers, personalized outreach highlighting products they've loved, exclusive VIP benefits to re-engage, and feedback surveys to identify and address issues.

ROI of churn prevention: Saving a customer costs $15-40 in retention offers/discounts while acquiring new customer costs $80-200 in advertising and acquisition costs—retention is 5-7x more cost-effective. High-value customers at risk of churn deserve aggressive retention investment up to 50% of their annual CLV.

Expected next purchase date predicts when individual customers will buy again based on personal purchase cycles—not calendar schedules. Fashion customer buys every 45 days on average → send promotional email day 38-42 when in-market. Coffee subscriber orders every 23 days → send reminder day 20 with expedited shipping offer. Vitamin buyer replenishes every 60 days → send subscription offer day 55 (before they run out).

Timing campaigns to predicted purchase dates achieves 43-67% higher conversion rates than calendar-based campaigns because customers receive offers exactly when considering purchase. Example: Pet supplies retailer uses predicted next purchase date for replenishment reminders. Dog food buyers get reminders 5 days before expected depletion based on package size and past order frequency. This achieves 68% conversion rate on reminder emails vs 12% on calendar-based "monthly specials"—467% improvement from behavioral timing.

Product affinity predictions use AI to recommend products customer doesn't know they want yet. Collaborative filtering identifies customers with similar purchase/browse history and recommends what they bought. Content-based filtering recommends products with similar attributes to past purchases. Hybrid approaches combine multiple algorithms for optimal accuracy. These AI recommendations achieve 25-45% higher click-through rates and 18-32% better conversion than manual curation.

Advanced Segmentation Strategies

Lifecycle stage automation creates dynamic segments that automatically update as customers progress: Prospects (subscribed but haven't purchased) receive welcome series building brand trust, educational content about products/category, social proof from existing customers, and conversion-focused offers (first purchase discount). Goal: convert to first-time buyer within 30 days.

First-Time Buyers (made one purchase, most critical retention moment) get post-purchase onboarding with product usage tips, cross-sell recommendations for complementary products, early loyalty program enrollment, and review requests (build social proof). Goal: drive second purchase within 60 days (customers who make second purchase have 54% higher LTV).

Active Customers (2+ purchases in last 90 days) receive ongoing engagement with new product announcements, exclusive offers for loyalty, category expansion campaigns, and referral program invitations. Goal: increase purchase frequency and category breadth.

VIP Customers (top 10% by revenue, frequency, or engagement) get white-glove treatment including early access to sales and new releases, exclusive products not available to general customers, concierge-level customer service, and special events or experiences. Goal: maintain satisfaction and prevent defection to competitors.

At-Risk Customers (haven't purchased in 90-180 days, or declining engagement) need proactive retention with win-back campaigns using compelling offers, feedback surveys to identify problems, reminder of past purchases and account value, and reduced email frequency (stop annoying them). Goal: re-activate before they're lost.

Lapsed Customers (180+ days inactive) receive final retention attempts with deep discounts or special promotions, survey about why they left, option to reduce email frequency rather than unsubscribe, and sunset warning if no engagement. Goal: recover 5-10% of lapsed customers or remove from list to protect deliverability.

Multi-dimensional segment examples: "Engaged West Coast Champions Who Love Dresses" = Lives in CA/OR/WA + opens 60%+ emails + RFM 4-5-5 + 80% of purchases are dresses. Send: New dress collection early access, exclusive West Coast pop-up event, VIP styling consultation.

"At-Risk Skincare Enthusiasts in Cold Climates" = RFM score declining + 70% past purchases skincare + lives in cold climate states. Send: Winter skincare protection tips, limited-time bundle discount on moisturizers, feedback survey about product satisfaction.

"High-Value New Customers Interested in Subscriptions" = First purchase over $150 + viewed subscription page + predicted high CLV. Send: Exclusive subscription offer (save 20%), guaranteed slot in monthly limited releases, free premium shipping forever.

Segmentation in Action: Campaign Examples

Product launch campaigns benefit massively from segmentation. Generic approach sends same product announcement to entire list achieving 18% open rate, 2.1% click-through rate, 0.8% conversion rate, and $0.32 revenue per email. Segmented approach targets only customers who've purchased similar products or shown category interest achieving 42% open rate (+133%), 8.7% click-through rate (+314%), 4.3% conversion rate (+438%), and $2.85 revenue per email (+791%).

Example: Skincare brand launching new serum. Segment 1: Past serum buyers (8,500 customers) → "Your favorite serum's new sister product" messaging → early access 48 hours before general release → achieved 51% open rate, 14% CTR, $43,200 revenue. Segment 2: Moisturizer buyers who haven't tried serums (12,000 customers) → "Upgrade your skincare routine" education-first messaging → intro offer bundle with moisturizer → 38% open, 9% CTR, $28,400 revenue. Generic blast to 50,000 would have generated $16,000—segmented approach generated $71,600, a 348% improvement.

Seasonal campaigns (Black Friday, holiday season) require sophisticated segmentation to maximize revenue. Early Bird Segment (VIP customers, high engagement): 72 hours early access before general sale, best deals reserved for them, exclusive products available, and limited quantities creating urgency. Achieves 62% open rate, 28% conversion rate, high AOV ($180+).

Deal Hunters (low engagement, price-sensitive, purchased mainly during sales): Day-of announcement with biggest discounts, scarcity messaging (limited time, selling fast), social proof (X people bought in last hour), and strong urgency (countdown timers). Achieves 32% open rate, 12% conversion rate, lower AOV ($85) but high volume.

Gift Givers (based on shipping to multiple addresses, gift message history): Holiday gift guides and curated bundles, gift wrapping and message services, bulk purchase discounts, and reminder emails about shipping deadlines. Achieves 45% open rate, 18% conversion rate, very high AOV ($240+).

Loyal Brand Fans (high RFM, brand advocates): Exclusive holiday products not available to public, limited edition or artist collaboration items, VIP shopping events or virtual parties, and early shipping guarantees. Achieves 58% open rate, 32% conversion rate, highest AOV ($320+).

Results: Segmented Black Friday campaign generates 2.8x more revenue per subscriber than generic "40% OFF EVERYTHING" blast to entire list while creating better customer experiences and reducing unsubscribe rates.

Implementation Roadmap: From Zero to Segmentation Master

Week 1: Foundation and Quick Wins starts with audit of current data quality ensuring Klaviyo properly tracking website events, purchase data flowing correctly, email engagement metrics accurate, and profile properties complete. Implement basic engagement segments dividing list into Engaged (opens 40%+), Moderate (20-40% opens), and Low (under 20% opens). Adjust email frequency by segment with Engaged receiving 6-8 emails/month, Moderate getting 4-5 emails/month, and Low receiving 2-3 emails/month. This alone typically improves overall engagement 15-25% and reduces unsubscribe rate 20-30%.

Week 2: Purchase Behavior creates RFM segments using Klaviyo's built-in RFM calculator, defines segments for Champions, Loyal, At-Risk, Lost, and develops segment-specific messaging strategies. Test one RFM-based campaign targeting Champions with VIP offer measuring open rates, conversion rates, and revenue per recipient vs control group.

Week 3: Product Affinity analyzes purchase history to identify top product categories, creates segments based on category preferences (segment size minimum 500 subscribers for statistical significance), and develops category-specific email campaigns. Launch first product affinity campaign promoting new products only to relevant segments (e.g., new running shoes to "runners" segment).

Week 4: Predictive Analytics enables Klaviyo's predictive analytics features (CLV prediction, churn risk, expected next purchase date), creates segments based on predicted behaviors (high-CLV prospects, at-risk customers, ready-to-purchase), and builds automated flows triggered by predictive scores. Example: At-risk customer flow triggers when churn risk exceeds 70%, sending personalized win-back sequence.

Month 2: Optimization and Scale includes A/B testing segment definitions and messaging, expanding number of active segments (aim for 15-25 well-defined segments), automating segment-based campaigns with flows, and training team on segment strategy and execution. Monthly review of segment performance including revenue per segment, engagement trends, segment migration patterns, and opportunities for refinement.

Ongoing: Continuous Improvement requires quarterly segment audits removing underperforming segments, merging similar segments, creating new segments based on insights, and updating messaging strategies. Monthly experimentation program testing new segmentation criteria, trying different messaging approaches, measuring incrementality and ROI, and documenting learnings. Annual strategic review recalibrating overall segmentation strategy, investing in new data sources or integrations, aligning segments with business goals, and setting targets for coming year.

Measuring Segmentation Success

Key performance indicators to track include revenue per email sent (primary metric—should increase 50-150% with proper segmentation), engagement rates by segment (open rates, click rates, conversion rates—segment-specific benchmarks), list health metrics (growth rate, unsubscribe rate, spam complaints, deliverability), and customer lifetime value by acquisition segment (are you attracting the right customers?).

Incrementality testing proves segmentation's value by running controlled experiments: Test group receives segmented campaigns while control group receives generic campaigns, running parallel for 90 days. Measure revenue difference, engagement lift, and cost savings. Calculate ROI as (incremental revenue - additional cost) / additional cost × 100.

Example: E-commerce brand runs 90-day incrementality test with 20,000 subscribers randomly split into test (segmented approach using 12 segments) and control (best-performing generic campaign to all). Test group generates $284,000 email-attributed revenue while control generates $118,000, showing +$166,000 incremental revenue (+141%). Additional cost for segmentation includes 15 hours/month strategy and execution time and no incremental platform cost (same Klaviyo plan). At $100/hour labor cost, incremental cost is $4,500. ROI = ($166,000 - $4,500) / $4,500 × 100 = 3,589% ROI from segmentation.

Segment health monitoring tracks segment size trends over time (are segments growing or shrinking?), migration patterns between segments (customers moving from At-Risk to Champions = success), engagement evolution within segments, and revenue contribution by segment. Flag problems early—if Champion segment is shrinking or At-Risk segment growing rapidly, intervention needed.

Common Segmentation Mistakes to Avoid

Over-segmentation creates too many tiny segments resulting in excessive complexity (50+ segments becomes unmanageable), segments too small for statistical significance (under 500 subscribers per segment reduces reliability), diluted messaging trying to personalize for every micro-segment, and team overwhelm managing countless campaigns. Solution: Start with 8-12 core segments, expand gradually to 15-25 max, combine similar segments, and focus on segments driving 80% of revenue.

Under-segmentation treats diverse customers as homogeneous with one-size-fits-all messaging ignoring subscriber preferences, wasted spend on wrong audiences, and missed opportunities for personalization. Solution: Minimum viable segmentation is Engaged vs Unengaged × Purchase History (4 segments). Build from there based on data.

Segmentation without action creates segments but sends same campaigns to everyone, defeating the entire purpose. Segments without tailored messaging waste time creating them with no performance improvement and confused team about segmentation value. Solution: Each segment needs distinct messaging strategy documented in segment definition. If you can't articulate unique approach for segment, don't create it.

Ignoring data quality builds segments on incomplete or inaccurate data leading to unreliable segments with wrong customers, campaign failures from bad data, and wasted effort on flawed foundation. Solution: Quarterly data audits checking profile completeness, purchase data accuracy, event tracking functionality, and integration health. Fix data issues before building complex segmentation.

Static segments that never update defines segments once and never revisits with customer behavior changing over time, segments becoming stale and irrelevant, and missing opportunities as business evolves. Solution: Monthly segment review analyzing performance trends, identifying segments needing updates, testing new segmentation criteria, and documenting changes.

Advanced Tools and Techniques

Klaviyo's segment builder provides powerful visual interface for drag-and-drop segment creation, 1,000+ customer properties to segment on, complex boolean logic (AND/OR/NOT operators), and predictive properties (CLV, churn risk, next purchase date). Advanced operators include "is set" / "is not set" (has/hasn't completed action), relative dates ("in the last X days", "more than X days ago"), ranges for numeric values, and nested conditions for complex logic.

Segment templates for fast implementation include VIP Customers (placed order in last 90 days AND total revenue > $500 AND email engagement > 60%), At-Risk Previously Active (placed order at least 2x AND last order > 90 days ago AND opens < 20% last 30 days), Browse Abandoners (viewed product in last 7 days AND did not add to cart AND opened email in last 30 days), and Price-Sensitive Buyers (purchased 3+ times AND 80%+ purchases during sales AND total revenue < $200).

API-driven dynamic segments for advanced users create segments programmatically via API, sync external data sources (CRM, analytics, custom databases), and trigger real-time actions based on segment membership. Example: Sync NPS survey scores from customer feedback tool → create segment of "Detractors" (NPS 0-6) → automatically trigger retention campaign within 24 hours.

Getting Expert Help

Most businesses achieve best results with professional segmentation strategy and implementation. Devaland's Klaviyo segmentation services include comprehensive data audit and cleanup, custom segment strategy for your business model, implementation of 12-25 high-value segments, automated flows triggered by segment membership, and ongoing optimization and testing. Typical results show 60-150% email revenue increase in 90 days, 35-50% improvement in engagement rates, and 20-40% reduction in list churn.

Packages start at $997/month including strategic planning and segment development, Klaviyo configuration and automation setup, campaign templates for each segment, training for your marketing team, and monthly performance reviews with optimization recommendations. One-time setup fee ($2,000-5,000) covers data cleanup and migration, comprehensive segment implementation, flow development for key segments, and team training workshops.

Book a consultation to audit your current segmentation approach, calculate improvement potential with segmentation scorecard, see segment examples from your industry, receive custom 90-day implementation roadmap, and get transparent ROI projections. Transform generic email blasts into precision-targeted campaigns that customers actually want to receive, dramatically improving both performance metrics and customer satisfaction while building a sustainable competitive advantage.