Tracking Key Performance Indicators (KPIs) and Metrics in Headless eCommerce. Essential eCommerce Metrics to Track!

Headless commerce aka Composable commerce has emerged as a disruptive new approach to building omnichannel digital shopping experiences. It decouples the frontend storefront from the backend commerce functionality using APIs. This allows for greater flexibility, scalability, and innovation velocity.

However, the complexity of headless commerce compared to monolithic platforms means that effectively tracking key performance indicators (KPIs) and metrics becomes even more critical for business success.

As composable commerce enables brands with loads of benefits and the ability to crush business goals, it's very important to track eCommerce KPIs and metrics to fully utilize the capabilities of a headless eCommerce platform and maximize eCommerce business success!

KPIs stands for key performance indicators are quantifiable measures that help evaluate the performance of business objectives. They go beyond vanity metrics to focus on data points directly aligning with core goals and strategy.

Some examples of KPIs are monthly recurring revenue, customer acquisition cost, cart abandonment rate, and return on ad spend.

Metrics more broadly encompass quantitative measures related to any business process or activity. They may not tie directly to strategic goals like KPIs. Page views, social media followers, and inventory turnover rate are common metrics.

KPIs reveal how well key objectives are being achieved while metrics provide granular performance data on operational aspects. KPIs derive actionable insights from metrics.

In headless commerce, measuring the right KPIs and metrics is crucial for several reasons:

• Identify Trends - KPIs reveal trends in business performance over time. Metrics provide supporting context.
• Diagnose Issues - KPIs and metrics help diagnose issues negatively impacting goals like conversions.
• Track Progress - KPIs quantify progress made towards objectives laid out in the business strategy.
• Guide Decisions - Metrics and KPIs enable data-driven decision-making on priorities and resource allocation.
• Optimize Strategies - KPIs pinpoint where existing strategies need refinement to improve outcomes.
• Benchmark Performance - KPIs allow bench-marking success against industry standards and competitors.
• Forecast the Future - Historical KPI data enables forecasting business growth and potential.

As headless commerce gains complexity with its decentralized nature, monitoring KPIs and metrics becomes vital for understanding what's working, what's not, and how to maximize success.

Gross Merchandise Value (GMV)

GMV measures the total sales dollar value of products sold through the headless platform over a defined period.

For example, if an online retailer sold $5 million worth of products in Q4 2022, their Q4 2022 GMV is $5 million. Comparing GMV quarter-over-quarter or year-over-year shows growth trends.

Average Order Value (AOV)

AOV is calculated by total revenue divided by total orders. If an online store generated $150,000 in revenue from 600 orders in May, its May AOV is $150,000/600 = $250.

Higher AOV means customers spend more per order on average. It can be increased with tactics like recommendations, bulk discounts, offers, etc.

Conversion Rate

Conversion rate is the percentage of site visitors that complete a target action. If an online store had 10,000 visitors last month, and 500 made a purchase, the conversion rate is 500/10,000 = 5%.

A low conversion rate suggests issues with user experience. A/B testing improvements, marketing and sales efforts, etc. help boost conversions.

Repeat Customer Rate

Repeat customer rate is the percentage of customers that return to purchase again. If a store has 200 repeat customers out of a total of 1,000 customers, the repeat customer rate is 200/1,000 = 20%.

A high repeat rate signifies loyal customers. Personalization and loyalty programs help increase repeat business.

Average Time to Checkout

The average time to checkout measures the time from cart to payment. eCommerce analytics tracks the checkout times and finds an average of 2 minutes, which indicates customers face minimal friction.

Lengthy average checkout times lead to higher abandonment. Streamlining payment options and pages reduces checkout duration.

Shopping Cart Abandonment Rate

The abandonment rate is calculated as carts without checkout divided by total carts. If there were 2,000 abandoned carts out of 5,000 total carts, the abandonment rate is 2,000/5,000 = 40%.

A high abandonment rate suggests issues in checkout trust or convenience. Implementing exit intent popups and other creative efforts reduces abandonment.

Customer Lifetime Value (CLV)

CLV totals how much revenue a customer generates during the relationship. If customers spend $400 annually, make 2 purchases annually, and stay for 5 years, CLV is $400 x 2 x 5 = $4,000.

Higher CLV allows for greater investment in acquisition. Loyalty programs improve CLV.

Customer Acquisition Cost (CAC)

CAC is marketing spend divided by new customers. If $20,000 was spent on marketing last month, and it acquired 400 new customers, CAC is $20,000/400 = $50.

Lower CAC shows cost-efficient acquisition. Improving conversion rates reduces CAC.

Customer Retention Rate

Retention rate is the percentage of customers retained over time. If 1,200 out of 1,500 customers from Q2 remained active in Q3, the retention rate is 1,200/1,500 = 80%.

Higher retention signifies satisfied customers. Ongoing loyalty rewards encourage retention.

Website Traffic

Website traffic is the number of visitors to the site over a period. An outdoor retailer had 150,000 site visits last August. Comparing traffic month-to-month and year-over-year shows growth.

Bounce Rate

The bounce rate is single-page visits divided by total visits. If an eCommerce site had 5,000 bounces out of 15,000 visits last week, the bounce rate is 5,000/15,000 = 33%.

Lower bounce rates indicate engaging content and user experience. Identifying high-bounce pages helps optimize them.

Social Media Engagement

Social engagement quantifies interactions on social platforms through likes, shares, comments, etc. A retailer with 50,000 Instagram followers and averaging 500 likes per post has a 1% engagement rate.

Higher social engagement suggests greater audience appeal. Benchmarking against competitors helps set goals.

Email Click-Through Rate

The click-through rate is the percentage of subscribers that clicked on campaigns. If an email was sent to 20,000 subscribers and had 2,000 clicks, the CTR is 2,000/20,000 = 10%.

A/B testing subject lines and content improves CTR. Industry benchmarks guide expectations.

Cost Per Click

Cost per click is advertising spend divided by clicks. If an ad campaign cost $3,000 and generates 15,000 clicks, the CPC is $3,000/15,000 = $0.2.

Lower CPC indicates cost-efficient ads. Comparing CPC across platforms and campaigns provides optimization insights.

Return on Ad Spend

Return on ad spend equals revenue divided by ad spend. If $10,000 was spent on ads last month, generating $50,000 in sales, the ROAS is $50,000/$10,000 = 5.

Higher ROAS means campaigns are productive. Reallocating budgets based on platform ROAS improves overall results.

Traffic to Lead Conversion Rate

Conversion rate is leads divided by traffic. If a retailer's blog received 100,000 visits last quarter and generated 2,000 leads, the conversion rate is 2,000/100,000 = 2%.

Higher conversion rates indicate engaging content and relevance to the audience.

Marketing Qualified Leads

Marketing-qualified leads are sales-ready leads nurtured by marketing. If the marketing team generated 500 MQLs last month, it shows their impact on the sales funnel.

Tracking lead quality over time ensures inbound strategies align with sales requirements.

Number of Sales

Total sales count indicates revenue and business growth. An electronics retailer had 2,000 sales in January 2023, up 10% from 1,800 sales in January 2022.

Setting sales targets and monitoring performance motivates sales teams to drive growth.

Sales Cycle Length

Sales cycle length measures the average time taken for a lead to convert to a customer. If the time between lead creation and purchase is 21 days on average, the sales cycle length is 21 days.

Shorter sales cycles imply efficient qualification and conversion processes. Streamlining sales stages accelerates deals.

Lead to Customer Conversion Rate

The lead-to-customer conversion rate is customers divided by leads. If a sales team converted 200 leads to 100 customers, the conversion rate is 100/200 = 50%.

Higher conversion rates signify positive lead nurturing and sales pitches. Training improves qualification skills. Also, the eCommerce sales dashboard comes in handy to view and analyze other sales metrics.

Monthly Recurring Revenue

Monthly recurring revenue (MRR) totals predictable recurring sales per month. A SaaS company with 500 customers paying $50 monthly subscriptions has $500 * $50 = $25,000 MRR.

Tracking MRR growth over time provides a metric of business sustainability.

Sales Pipeline Value

Sales pipeline value is the total expected revenue from prospects in the pipeline. 100 deals worth a potential $2M in the pipeline signifies $2M worth of upcoming opportunities.

Higher pipeline values indicate abundant sales prospects on the horizon. Strong pipelines increase revenue predictability.

Sales Team Utilization

Utilization tracks time spent on productive selling activities versus non-selling tasks. If sales reps spend 50% of their time on calls, emails, and meetings, utilization is 50%.

Higher utilization improves sales productivity. Reducing admin overhead boosts utilization.

Load Times/Page Speed

Page load time measures how fast pages render. If the homepage load time is 2.5 seconds on average, it indicates fast content delivery.

Faster load times reduce bounce rates and improve conversions. Optimizing images, JS, and CSS improves speed.

Server Response Time

Server response time tracks backend API latency. An average response time of 50ms signifies highly performant APIs.

Lower response times speed up page delivery and improve user experience. Caching and scaling optimize response times.

Site Uptime/Downtime

Uptime measures the percentage of time a site is accessible to visitors. 99.95% uptime means high availability with negligible downtime.

Higher uptime prevents revenue loss. Auto-scaling infrastructure improves fault tolerance.

CDN Performance

CDN metrics like cache hit ratio indicate optimization. A 90% hit ratio means most content is served from edge caches, reducing origin traffic.

Tuning edge logic improves cache hits. Monitoring origin traffic quantifies CDN offload gains.

API Availability

API availability tracks the uptime percentage for backend APIs. If APIs have 99.9% availability, it ensures reliability.

Higher availability means uninterrupted data access for the frontend. Load balancing and redundancies prevent downtime.

API Latency

API latency measures response times for backend API calls. An average latency of 100ms indicates performant APIs.

Lower latency improves frontend responsiveness. Scaling API resources optimizes latency.

API Error Rate

The API error rate monitors failed API requests. A 1% error rate signifies robust APIs with minimal downtime.

Lower error rates reflect reliable infrastructure. Monitoring spikes helps address instability.

API Throttle Rate

The API throttle rate tracks requests throttled for exceeding usage limits. A 2% throttle rate prevents excessive load.

Appropriate throttling ensures system stability. Tuning thresholds balances traffic.

Ticket Resolution Time

Resolution time measures how quickly support tickets are resolved. An average resolution time of 24 hours indicates excellent responsiveness.

Faster resolution improves customer satisfaction. Prioritizing tickets by severity optimizes resolution times. This is one of the most important customer service KPIs.

Customer Satisfaction Score

Customer satisfaction (CSAT) surveys quantify satisfaction on a numeric scale. An average score of 4.7 out of 5 suggests most customers are highly satisfied.

A higher CSAT indicates happier customers. Identifying drivers of satisfaction and dissatisfaction guides improvements.

Net Promoter Score

Net Promoter Score (NPS) measures customer loyalty based on the likelihood of recommendation. A NPS of 70% is considered excellent.

Higher promoters boost growth through referrals. Gathering open-ended feedback provides insights into improving NPS.

Customer Churn Rate

The churn rate shows the percentage of customers lost over a period. A churn rate of 3% is considered low for eCommerce. Lower churn nurtures retention. Analyzing reasons for churn enables recovery initiatives.

Customer Complaint Rate

The complaint rate represents the percentage of support cases stemming from negative experiences. A low complaint rate of 5% suggests minimal issues.

Fewer complaints indicate smooth customer journeys. Complaint spikes help identify problem areas.

First Contact Resolution Rate

First contact resolution measures support tickets resolved in the first interaction. A high 85% resolution rate minimizes revisits. Higher first-contact resolution improves efficiency and satisfaction. Knowledge bases support fast answers.

Improving Site Performance

For example, an outdoor retailer improved site speed by 50% by optimizing images which increased conversions by 15%.

Reducing Cart Abandonment

Cart abandonment can be reduced by streamlining the checkout process, offering guest checkout options, and using exit intent popups to capture abandoning users.

A home goods company reduced abandonment by 8% by simplifying checkout which generated 6% more revenue.

Increasing Order Value

Order values can be increased by recommending complementary products, offering bulk order discounts or free shipping above thresholds, and providing loyalty rewards or tokens to frequent purchasers.

A fashion brand increased average order value by 10% by showcasing styled looks and offering discounts on 3+ items.

Lowering Customer Acquisition Costs

Customer acquisition costs can be lowered by targeting high-intent audience segments, promoting repeat purchases through loyalty programs, and correctly attributing sales to marketing channels.

An electronics retailer optimized ads to target previous high-AOV customers reducing CAC by 15%.

Building Customer Loyalty

Loyalty can be built by providing excellent post-purchase support, implementing VIP loyalty programs, sending retention offers, and seeking customer feedback to act on pain points. This also adds to the eCommerce conversion rate and tracks their performance.

A specialty retailer strengthened retention by 25% through a tiered loyalty program offering free expedited delivery and discounts.

Right-sizing Infrastructure

Infrastructure can be right-sized by monitoring traffic, storage, and API usage patterns to optimize hosting, CDNs, and caching for ideal capacity without over-provisioning.

An automotive parts supplier reduced cloud hosting costs by 30% by shuttering unused production microservices and database instances.

Monitoring Usage and Traffic

Tracking usage metrics helps forecast growth and seasonal peaks. For example, an outdoor retailer correlates inventory to web traffic to plan for demand surges in summer.

Automating Workflows

Automating order processing, post-purchase emails, inventory updates between systems, and other workflows improves operational efficiency.

A wholesaler automated the stock update process between order management and ERP cutting fulfillment time by 20%.

Headless commerce removes barriers to delivering personalized omnichannel customer experiences. Careful eCommerce tracking across marketing, sales, technology, and customer experience becomes imperative.

KPIs like conversion rate, average order value, customer lifetime value, and net promoter score provide data-backed insights into what's working well and what needs improvement. Granular metrics diagnose the reasons behind KPI fluctuations.

Optimizing site performance, reducing cart abandonment, lowering acquisition costs, and building loyalty is key to maximizing success. The decentralized nature of headless commerce means relying on metrics and KPIs for data-driven decision-making is vital.

Get started with your headless commerce journey and get explosive growth.

At WPSteroids, our MACH experts help you with:

• Identify the right metrics and KPIs tailored to your strategic objectives
• Instrument data collection across all touchpoints
• Build executive dashboards and reports to monitor performance
• Set targets based on historical data and industry benchmarks
• Identify optimization opportunities to improve results
• Track progress over time as you scale your headless implementation

With our unified commerce solution combining the best headless technologies and strategic expertise, we empower leading retailers to deliver engaging customer experiences anywhere while maximizing business success.

Don’t wait, take action. Book your project discovery call now!