SaaS Marketing - 8 Benchmarks to Drive Growth

Contents

Benchmark 1: Direct Traffic Share
Benchmark 2: Organic Search Share
Benchmark 3: AI Referral Share
Benchmark 4: Visitor-to-Lead
Benchmark 5: Lead-to-MQL
Benchmark 6: MQL-to-SQL
Benchmark 7: SEO
Benchmark 8: Email
Turn SaaS Marketing Data into Your Next Growth Advantage
Scale Revenue Faster with MarketEngine’s AI-Powered SaaS Marketing Engine
Frequently Asked Questions

Stop guessing what drives growth. Discover the benchmarks that turn traffic into qualified leads, stronger pipelines, and predictable SaaS revenue.

Which marketing benchmarks should a B2B SaaS company track?

US B2B SaaS teams should track traffic by source, visitor-to-lead conversion, lead-to-MQL and MQL-to-SQL rates, AI referral performance, SEO contribution, and email conversions. Together, these marketing benchmarks connect acquisition activity with pipeline outcomes for growth.

Your SaaS dashboard shows rising traffic, but is your pipeline growing at the same pace? For mid-market B2B SaaS companies in the US, more visitors, higher email engagement, and increased AI referrals mean little if they fail to translate into qualified leads and revenue.

The challenge is knowing what good performance actually looks like. Without reliable SaaS marketing benchmarks, marketing teams risk investing in channels that generate activity but fail to move prospects toward a purchase. Meanwhile, changing search behavior, longer buying journeys, and growing competition for decision-makers make historical assumptions increasingly unreliable.

Effective mid-market SaaS marketing requires more than tracking isolated metrics. It means understanding how your traffic sources, conversion rates, and marketing channels compare with relevant industry benchmarks, and how each contributes to pipeline growth.

This guide explores 8 essential marketing benchmarks for US B2B SaaS companies to help you identify performance gaps and make smarter growth decisions.

Here are the 8 benchmarks we will talk about:

Direct traffic share
Organic Search Share
AI Referral Share
Visitor-to-Lead
Lead-to-MQL
MQL-to-SQL
SEO
Email

SaaS Marketing Challenge	MarketEngine’s AI Agentic Services	Expected Result
Unclear traffic source performance	AI-powered traffic analysis and channel tracking	Better acquisition insights
Low organic search visibility	Agentic SEO research and content optimization	Increased relevant organic traffic
Limited visibility into AI referrals	AI search monitoring and citation optimization	Improved AI discovery
Low visitor-to-lead conversion	Landing-page analysis and conversion optimization	More qualified leads
Poor lead qualification rates	Funnel analysis and lead nurturing support	Better MQL and SQL progression
SEO activity disconnected from revenue	Performance tracking and pipeline analysis	Clearer marketing ROI
Weak email campaign performance	AI-assisted email optimization and audience segmentation	Higher engagement and conversions

Let’s get started!

Benchmark 1: Direct Traffic Share

Direct traffic share measures the percentage of website visits to a mid-market B2B SaaS company’s website that analytics tools attribute to direct traffic. These visits may come from people typing a URL, using bookmarks, or arriving without identifiable referral information, including some untracked marketing activity.

Why Does Direct Traffic Share Matter?

Strong direct traffic can indicate buyers remember your company and return independently.
Untracked visits can distort channel reports and mislead budget allocation decisions.
SaaS buyers may revisit your website after reviewing several competing software solutions.
Reliable attribution helps SaaS marketing teams distinguish brand demand from tracking gaps.

How to Track Direct Traffic Share

Open Google Analytics 4 (GA4) and navigate to Reports → Acquisition → Traffic acquisition.
Select Session default channel group to identify sessions attributed to Direct.
Compare Direct sessions with total website sessions for the same reporting period.
Review campaign tagging and referral data to identify traffic incorrectly classified as Direct.

Google Analytics classifies traffic as Direct when it cannot identify a clear referral source; this includes genuine direct visits and some poorly tracked campaigns.

How to Calculate Direct Traffic Share

Formula:

Direct Traffic Share =

Direct Sessions Total Sessions

× 100

Divide the number of sessions attributed to Direct by all website sessions during the same period, then multiply by 100. Use consistent reporting dates and channel definitions when comparing your results.

Example: If a SaaS marketing team records 20,000 total website sessions in a month, including 8,000 Direct sessions:

8,000 20,000

× 100 = 40%

Its direct traffic share is 40%. However, this figure alone does not prove strong brand recognition; missing tracking data may also contribute.

Note: The examples use hypothetical figures to demonstrate how each marketing metric is calculated.

How to Improve Direct Traffic Share

For mid-market SaaS marketing teams, the goal should not be to increase Direct traffic at any cost. These marketing benchmarks are most useful when they help you understand brand demand and improve attribution quality.

Improvement area	What to do	Expected benefit
Brand awareness	Build recognition through relevant industry content and events.	More repeat and intentional visits
Campaign tracking	Add consistent UTM parameters to email and campaign links.	Fewer visits misclassified as Direct
Customer retention	Share useful product updates and customer resources.	More returning visitors
Referral tracking	Check redirects and referral exclusions in GA4.	More accurate channel reporting
Performance review	Compare Direct share with conversions and branded search trends.	Better understanding of brand demand

Benchmark 2: Organic Search Share

Organic search share measures the percentage of a mid-market B2B SaaS company’s website sessions that come from unpaid search engine results. For SaaS marketing teams, it shows how much website discovery depends on search visibility rather than paid campaigns, referrals, email, or direct visits over a defined reporting period.

Why Does Organic Search Share Matter?

It shows whether unpaid search consistently introduces potential buyers to your product.
Strong organic reach can reduce dependence on paid acquisition over time.
Search visits reveal which problems and solutions attract active buyer interest.
Tracking trends helps teams prioritize content investments and spot visibility losses.

How to Track Organic Search Share

Open GA4 and navigate to Reports → Acquisition → Traffic acquisition.
Filter sessions by the Organic Search channel group.
Compare organic sessions against total website sessions for the same period.
Use Google Search Console to review clicks, queries, and landing-page performance.
Separate branded and non-branded search traffic to understand discovery patterns.

How to Calculate Organic Search Share

Formula:

Organic Search Share =

Organic Search Sessions Total Website Sessions

× 100

Divide the number of sessions from unpaid search results by total website sessions during the same period, then multiply by 100. Keep the reporting period and channel definitions consistent when comparing results.

Example: Suppose a US mid-market B2B SaaS company receives 50,000 website sessions in a month, of which 15,000 come from organic search.

15,000 50,000

× 100 = 30%

Its organic search share is 30%. This indicates that organic search accounts for nearly one-third of its website traffic, but it does not establish whether that traffic generates qualified leads or revenue.

Note: The examples use hypothetical figures to demonstrate how each marketing metric is calculated.

How to Improve Organic Search Share

For mid-market SaaS marketing teams, increasing organic search share should mean attracting relevant buyers, not simply publishing more content. These marketing benchmarks help identify whether search visibility is expanding and where improvements may create commercial value.

Improvement area	What to do	Expected benefit
Search intent	Target queries linked to product problems and buying needs.	More relevant organic visitors
Solution pages	Build focused pages for use cases and customer industries.	Better visibility for commercial searches
Content quality	Publish useful comparisons, guides, and original research.	Greater relevance and search reach
Technical SEO	Fix indexing issues, broken links, and slow pages.	More pages eligible to appear in search
Performance analysis	Review organic leads, conversions, and non-branded clicks monthly.	Clearer insight into business impact

Benchmark 3: AI Referral Share

AI referral share measures the percentage of a B2B SaaS website’s sessions that arrive through links from AI platforms such as ChatGPT, Perplexity, and Gemini. For SaaS marketing teams, it shows how much measurable website traffic AI-powered discovery contributes during a chosen reporting period.

Why Does AI Referral Share Matter?

It shows whether AI platforms are sending potential buyers to your website.
Referral trends reveal which AI discovery sources contribute measurable website visits.
Comparing conversions helps separate traffic volume from meaningful buying interest.
These marketing benchmarks help teams evaluate an emerging acquisition channel responsibly.

How to Track AI Referral Share

In GA4, open Reports → Acquisition → Traffic acquisition.
Filter referral sessions from identifiable AI platforms and domains.
Use consistent UTM tags for campaigns shared through AI-related channels.
Compare AI referrals by landing page, conversion, and reporting period.

How to Calculate AI Referral Share

Formula:

AI Referral Share =

AI-Referred Sessions Total Website Sessions

× 100

For SaaS marketing teams, divide sessions attributed to identifiable AI platforms by total website sessions for the same period, then multiply by 100. This calculation provides one of the marketing benchmarks for assessing AI-driven website discovery.

Example: A US B2B SaaS company records 25,000 website sessions in a month, including 1,000 sessions from AI platforms.

1,000 25,000

× 100 = 4%

Its AI referral share is 4%. This measures identifiable referral traffic, not every visitor who discovered the company through an AI answer.

Note: The examples use hypothetical figures to demonstrate how each marketing metric is calculated.

How to Improve AI Referral Share

For mid-market SaaS marketing teams, the goal is to earn relevant AI-referred visits, not simply increase the percentage. Track whether these visitors explore product pages, request demos, or become qualified leads before deciding which activities deserve further investment.

Improvement area	What to do	Expected benefit
Buyer-focused content	Answer specific product and industry questions clearly.	More opportunities for AI discovery
Original research	Publish unique data, insights, and useful comparisons.	Stronger reasons for AI systems to reference your content
Third-party presence	Maintain credible profiles and relevant industry mentions.	More opportunities to be discovered during buyer research
Website structure	Use descriptive headings and clearly explained product features.	Easier interpretation of your expertise
Referral analysis	Review AI sources, landing pages, and conversions monthly.	Better decisions about future SaaS marketing investments

How do I measure AI referral traffic and its value for SaaS marketing?

Measure AI referral share by dividing sessions from identifiable AI platforms by total website sessions. Track conversions from those visits separately, because referral volume alone cannot show whether AI discovery attracts relevant SaaS buyers overall.

Benchmark 4: Visitor-to-Lead

Visitor-to-lead conversion rate measures the percentage of website visitors who share their details through a demo request, trial sign-up, or contact form. For mid-market B2B SaaS companies, it shows how effectively website content and landing pages turn potential buyers into identifiable leads.

Why Does Visitor-to-Lead Conversion Matter?

It reveals whether website visitors find your offer relevant enough to act.
Strong conversion rates help SaaS marketing teams use existing traffic more effectively.
Comparing landing pages highlights which messages attract potential buyers most successfully.
Tracking this metric connects website activity with lead generation and pipeline growth.

How to Track Visitor-to-Lead Conversion

Open GA4 and review landing-page performance and conversion events.
Track demo requests, trial sign-ups, and contact form submissions separately.
Compare unique visitors and leads over the same reporting period.
Connect CRM records to identify which leads become qualified opportunities.

How to Calculate Visitor-to-Lead Conversion Rate

Formula:

Visitor – to – Lead Rate =

Unique Leads Unique Website Visitors

× 100

Divide the number of unique visitors who become leads by the total number of unique website visitors during the same period, then multiply by 100. For accurate SaaS marketing reporting, define which actions count as leads and avoid counting repeat submissions as new leads.

Example: A B2B SaaS website receives 10,000 unique visitors in a month, and 300 become leads.

300 10,000

× 100 = 3%

The visitor-to-lead conversion rate is 3%.

Note: The examples use hypothetical figures to demonstrate how each marketing metric is calculated.

How to Improve Visitor-to-Lead Conversion

These marketing benchmarks help mid-market SaaS marketing teams identify friction points and prioritize changes that encourage relevant visitors to take action.

Improvement area	What to do	Expected benefit
Landing-page relevance	Match page messaging to the visitor’s search intent.	More relevant enquiries
Calls to action	Use clear, specific CTAs such as “Book a Demo.”	More completed actions
Form design	Request only the information needed at this stage.	Fewer abandoned forms
Trust signals	Add customer reviews, security details, and verified results.	Greater willingness to engage
Conversion testing	Test page headlines, layouts, and offers systematically.	Evidence-based conversion improvements

What is a good visitor-to-lead conversion rate for B2B SaaS?

There’s no single conversion rate that suits every SaaS company. Compare your visitor-to-lead rate with past performance, traffic intent, product price, and sales model; then assess whether leads progress into qualified opportunities and revenue consistently.

Benchmark 5: Lead-to-MQL

Lead-to-MQL conversion rate measures the percentage of leads that meet a company’s marketing-qualified lead (MQL) criteria. For mid-market B2B SaaS companies, it shows how effectively initial enquiries become prospects who match the target customer profile and demonstrate enough interest to warrant further marketing and sales attention.

Why Does Lead-to-MQL Conversion Matter?

It reveals whether campaigns attract prospects who fit your ideal customer profile.
Consistent qualification criteria help SaaS marketing teams compare lead quality across channels.
A low rate may indicate weak targeting or unclear qualification rules.
Tracking progression helps teams prioritize leads more likely to become customers.

How to Track Lead-to-MQL Conversion

Define MQL criteria with sales, including fit, interest, and engagement.
Track lead and MQL status changes in your CRM.
Segment MQL conversions by channel, campaign, and customer type.
Compare leads created with MQLs generated during the same period.

How to Calculate Lead-to-MQL Conversion Rate

Formula:

Lead – to – MQL Rate =

Leads Becoming MQLs from a Cohort Total Leads in That Cohort

× 100

Track a group of leads created during the same period and measure how many eventually meet your marketing-qualified lead criteria. This avoids misleading results when leads take different amounts of time to qualify.

Example: Of 500 leads generated in January, 125 become MQLs within 60 days.

125 500

× 100 = 25%

The cohort’s lead-to-MQL conversion rate is 25% within 60 days.

Note: The examples use hypothetical figures to demonstrate how each marketing metric is calculated.

How to Improve Lead-to-MQL Conversion

These marketing benchmarks help mid-market SaaS marketing teams understand whether their campaigns attract suitable prospects and move them toward meaningful sales conversations.

Improvement area	What to do	Expected benefit
Lead targeting	Focus campaigns on industries and companies matching your ideal customer profile.	Better-fit leads
Qualification criteria	Agree on clear MQL rules with sales teams.	More consistent lead assessment
Lead nurturing	Share relevant case studies, guides, and product education.	Stronger buying interest
Lead scoring	Combine company fit with meaningful engagement signals.	Better prioritization
Feedback loops	Review rejected MQLs with sales and adjust targeting.	Fewer unsuitable leads

Benchmark 6: MQL-to-SQL

MQL-to-SQL conversion rate measures the percentage of marketing-qualified leads that sales accepts as sales-qualified leads (SQLs) for further evaluation. For B2B SaaS companies in the US, it shows whether marketing is delivering prospects who fit sales criteria and demonstrate sufficient buying intent to justify direct sales engagement.

Why Does MQL-to-SQL Conversion Matter?

It reveals whether marketing-qualified prospects meet sales expectations and requirements.
Strong alignment helps SaaS marketing teams reduce wasted sales effort.
A low rate can expose gaps in targeting or qualification criteria.
Tracking progression helps teams improve lead handoffs and pipeline efficiency.

How to Track MQL-to-SQL Conversion

Define SQL criteria jointly with sales and marketing teams.
Track MQL-to-SQL status changes in your CRM.
Segment conversions by campaign, channel, industry, and company size.
Review sales rejection reasons to identify recurring qualification gaps.

How to Calculate MQL-to-SQL Conversion Rate

Formula:

MQL – to – SQL Rate =

MQLs Accepted as SQLs Total MQLs in the Same Cohort

× 100

Measure how many MQLs from the same starting group are accepted by sales as SQLs within a defined period. Use a consistent SQL definition agreed upon by marketing and sales.

Example: Of 200 MQLs created in January, 70 become SQLs within 45 days.

70 200

× 100 = 35%

The cohort’s MQL-to-SQL conversion rate is 35% within 45 days.

Note: The examples use hypothetical figures to demonstrate how each marketing metric is calculated.

How to Improve MQL-to-SQL Conversion

These marketing benchmarks help mid-market SaaS marketing teams identify gaps between lead qualification and sales acceptance, enabling more focused improvements.

Improvement area	What to do	Expected benefit
Qualification criteria	Agree on shared MQL and SQL definitions.	More consistent lead handoffs
Lead targeting	Focus on companies matching your ideal customer profile.	Better sales acceptance
Handoff speed	Route qualified leads to sales promptly.	Less lost buying interest
Sales feedback	Record why leads are accepted or rejected.	Clearer targeting improvements
Nurturing	Address missing information before sales outreach.	Better-prepared prospects

How can SaaS companies connect marketing performance to revenue?

Connect analytics with your CRM to track leads from their original marketing source through qualification, opportunities, and closed deals. This helps SaaS marketing teams assess channel contribution and prioritize spending based on pipeline value wisely.

Benchmark 7: SEO

SEO measures how effectively a B2B SaaS company’s website attracts relevant visitors through unpaid search results and turns them into potential customers. For SaaS marketing teams, the most useful indicators include organic traffic, search visibility, qualified leads, and pipeline generated from organic search.

Why Does SEO Performance Matter?

Organic search connects your product with buyers actively researching solutions.
Strong search visibility can reduce dependence on paid acquisition over time.
Qualified organic leads reveal whether content attracts relevant potential customers.
Pipeline tracking connects search performance with business growth and revenue.

How to Track SEO Performance

Use Google Search Console to monitor impressions, clicks, and search queries.
Review organic sessions and landing pages in GA4.
Track demo requests, trials, and qualified leads from organic search.
Connect CRM records to identify organic-sourced opportunities and revenue.

How to Calculate SEO Conversion Rate

Formula 1:

Organic Visitor – to – Lead Rate =

Organic Leads Organic Visitors

× 100

Divide the number of leads generated from organic search by the number of organic visitors during the same period, then multiply by 100. For SaaS marketing teams, this connects search traffic with lead generation rather than treating rankings as the final measure of success.

Example: A SaaS website receives 12,000 organic visitors in a month and generates 360 leads from them.

360 12,000

× 100 = 3%

The organic visitor-to-lead conversion rate is 3%. This metric should be reviewed alongside lead quality and pipeline contribution to understand commercial impact.

How to Calculate SEO-Sourced Pipeline Contribution

Formula 2:

SEO Pipeline Share =

Pipeline Value Sourced by Organic Search Total New Pipeline Value

× 100

Use your CRM to identify new sales opportunities attributed to organic search as the originating channel. Divide their total potential contract value by the total new pipeline value created during the same period. Keep attribution rules consistent and separate sourced pipeline from influenced pipeline.

Example: Organic search generates $240,000 in new pipeline, while the company generates $1.2 million overall.

$240,000 $1,200,000

× 100 = 20%

SEO accounts for 20% of newly created pipeline value.

Note: The examples use hypothetical figures to demonstrate how each marketing metric is calculated.

How to Improve SEO Performance

A focused mid-market SaaS marketing strategy should prioritize qualified organic demand rather than traffic volume alone. Review these marketing benchmarks monthly to identify which pages attract suitable buyers and which need improvement.

Improvement area	What to do	Expected benefit
Search intent	Target queries that reflect product needs and buying stages.	More relevant organic visitors
Product pages	Explain features, use cases, and business value clearly.	Better commercial search relevance
Content quality	Publish useful comparisons, guides, and original research.	Stronger search visibility
Technical SEO	Fix indexing issues, broken links, and slow pages.	Better access for search engines
Conversion tracking	Connect organic leads with CRM opportunities and impact revenue.	Clearer business opportunities and impact revenue.

Benchmark 8: Email

Email marketing performance measures how effectively a B2B SaaS company uses email to engage subscribers, nurture prospects, encourage product trials, and support customer retention. For SaaS marketing teams, key indicators include click-through rates, conversions, unsubscribes, and revenue influenced by email campaigns.

Why Does Email Performance Matter?

Email nurtures prospects who need more information before choosing software.
Engagement metrics help SaaS marketing teams improve message relevance and timing.
Conversion tracking reveals which campaigns generate trials, demos, and purchases.
Retention emails support product adoption, renewals, and long-term customer value.

How to Track Email Performance

Monitor delivery, clicks, unsubscribes, and conversions in your email platform.
Segment reports by campaign type, audience, and lifecycle stage.
Use tagged links to attribute website visits and conversions accurately.
Connect email engagement with CRM records to track pipeline influence.

How to Calculate Email Conversion Rate

Formula:

Click – to – Conversion Rate =

Unique Clickers Who Convert Unique Email Clickers

× 100

This measures how effectively an email persuades people who click through to complete the intended action, such as booking a demo or starting a trial. It isolates post-click performance more effectively than dividing conversions by all delivered emails.

Example: Of 800 unique people who click an email, 96 register for a free trial.

96 800

× 100 = 12%

The email click-to-conversion rate is 12%. Use consistent attribution rules and reporting periods when comparing campaigns.

Note: The examples use hypothetical figures to demonstrate how each marketing metric is calculated.

How to Improve Email Performance

These marketing benchmarks help SaaS marketing teams identify which campaigns encourage meaningful action and which need refinement.

Improvement area	What to do	Expected benefit
Audience segmentation	Group subscribers by role, behavior, and buying stage.	More relevant messages
Subject lines	Test specific, accurate subject lines that match email content.	Better engagement
Email content	Focus on one useful message and one clear CTA.	More clicks and conversions
Send timing	Test delivery times using audience engagement data.	Improved response
Conversion tracking	Measure demos, trials, and revenue—not open alone.	Better performance insights

Turn SaaS Marketing Data into Your Next Growth Advantage

Sustainable SaaS growth depends on understanding which marketing activities attract the right buyers, convert them into qualified leads, and contribute to revenue. Tracking traffic sources alone is not enough; businesses must also measure lead progression, search performance, AI referrals, and email conversions to identify what drives results.

The right marketing benchmarks help US B2B SaaS companies compare performance, uncover weaknesses, and allocate budgets where they can deliver greater business value. However, industry averages should guide decisions, not dictate them. Your product, target audience, pricing, and sales cycle all influence what good performance looks like.

By combining reliable measurement with continuous testing, your SaaS marketing team can make informed decisions, strengthen pipeline performance, and build a more predictable path to growth.

Scale Revenue Faster with MarketEngine’s AI-Powered SaaS Marketing Engine

MarketEngine combines AI-powered execution with human marketing expertise to help B2B SaaS companies accelerate growth. From content and SEO to campaign execution, its integrated approach helps teams reduce manual work and focus on measurable outcomes.

SEO & AEO: Improve visibility across Google and AI search platforms.
Content Creation: Publish relevant content that attracts and educates potential buyers.
Integrated Marketing: Connect content, social, email, and digital campaigns.
Performance Analysis: Identify conversion gaps and improve marketing results.

With AI-powered execution and human expertise, MarketEngine helps SaaS teams move beyond traffic growth and focus on qualified leads and measurable pipeline outcomes.

Ready to improve your marketing performance?

Book a Free Growth Call Now!

Naren Patil

Founder & CEO, MarketEngine

Naren Patil is the former GM and Head of Product Marketing at Saba Learning, a $100 million business. He also served as SVP of Marketing and Demand Generation at NGDATA, Director of Product Marketing at Oracle, and Head of Product at TriNet.

Naren has spoken at TiECon Silicon Valley, Northwestern Kellogg, TiE Atlanta, and TiE Mumbai, and has been featured in publications such as Forbes. He holds an MBA from the Kellogg School of Management at Northwestern University.

Frequently Asked Questions

1. How do I know if my SaaS marketing performance is actually good compared with competitors?

Compare your results with relevant US B2B SaaS industry data, but account for company size, pricing, sales cycle, and business model. Use marketing benchmarks alongside your historical performance to identify meaningful gaps rather than treating industry averages as universal targets.

2. What if my website traffic is growing but I’m not generating enough qualified leads?

Growing traffic does not guarantee stronger lead generation. Review visitor-to-lead conversion rates, traffic sources, landing-page relevance, and lead quality. Identify which channels attract potential buyers and improve pages that receive relevant traffic but generate few enquiries.

3. Should I invest in AI search optimization if AI referrals currently contribute very little traffic?

Not necessarily at the expense of established channels. First, measure identifiable AI referrals, their conversion rates, and the buying intent they demonstrate. Test useful, evidence-backed content and monitor results over time before shifting significant budget away from proven acquisition channels.

4. How can I measure marketing ROI when leads take months to become customers?

Connect analytics and CRM data to follow leads from their original source through qualification, sales opportunities, and closed deals. Review cohort-based conversion rates and pipeline value so you can assess progress before the full sales cycle ends. Consistent attribution rules help prevent misleading ROI calculations.

5. Which SaaS marketing metrics should I prioritize if my team has limited time and budget?

Start with qualified leads, visitor-to-lead conversion, MQL-to-SQL progression, and pipeline generated by each major channel. Add organic search, email, and AI referral metrics where relevant. Effective SaaS marketing measurement prioritizes indicators tied to revenue, while marketing benchmarks help reveal which improvements deserve attention first.