How to Analyse Conversion Paths and Customer Journeys

The Paths dashboard is SourceLoop’s multi-touch attribution view in its purest form. Instead of assigning credit to channels and summarising, it shows you the exact sequence of touches every converting visitor went through, the literal path to conversion.

It’s the dashboard for the question every marketer eventually asks: “Is paid social actually driving sales, or just creating awareness that organic search converts later?” The Paths view answers it directly.

What the Paths dashboard answers

In one screen:

• The single-touch paths that close in one visit (high-intent traffic)
• The two- and three-touch paths that compound (your real conversion funnel)
• Which channels reliably assist conversions even when they’re not the closer
• The exact sequence your highest-revenue customers go through before they convert
• Whether your funnel has a repeating discovery → consideration → close pattern (and what each role plays)

It’s the right dashboard when you need to defend or kill a channel based on its assist value, plan retargeting, or design a nurture sequence that mirrors real buyer behaviour.

Step 1: Pick your filters

The filter bar is similar to the other dashboards but with one new control specific to Paths:

1. Date range — defaults to the last 30 days
2. Collapse repeat touches — toggle in the top-right (covered in detail below); ON by default
3. Filter — add ad-hoc filters on channel, source, campaign, country, device, etc.

The dashboard recomputes the entire view on every filter change.

Step 2: Decide whether to collapse repeat touches

The Collapse repeat touches toggle in the top-right is one of the most important controls on this dashboard. It changes what each path actually looks like:

• ON (default) — repeated touches from the same channel collapse into one. A visitor who hits your site three times from social and converts shows up as 1 social instead of 1 social → 2 social → 3 social. Use this when you want to see the structural path: what unique sequence of channels matters.
• OFF — every individual session is a separate touch. The same visitor shows as 1 social → 2 social → 3 social. Use this when you specifically want to see frequency patterns: how many touches a channel needs before it converts.

For most analysis (budget allocation, channel mix decisions), ON is the right default. Flip it OFF when investigating ad-frequency or nurture-cadence questions.

Step 3: Switch grouping with the tabs

Above the table, seven tabs control what each touch in the path represents:

• Channel — high-level bucket (social, paid_search, referral, email, etc.) — the default
• Source — literal utm_source value (google, linkedin, twitter, etc.)
• Medium — literal utm_medium value (cpc, organic, social, email, etc.)
• Campaign — literal utm_campaign value (e.g., “summer-sale-2026”)
• Term — utm_term, often keywords from paid search
• Content — utm_content, often ad-variant identifiers
• Page — landing pages on your site, so each touch is a specific URL instead of a channel

The Page tab is especially powerful for content marketing analysis, it tells you the literal sequence of pages each converter read on the way to the conversion, like “1 /blog/utm-tracking → 2 /pricing → 3 /demo-thank-you”.

Switch tabs based on the question you’re answering:

• “Which channel mixes convert?” → Channel tab
• “Which specific Google Ads campaign features in winning paths?” → Campaign tab
• “What content sequence do my best customers read?” → Page tab
• “Which keywords appear in paid-search-assisted paths?” → Term tab

Step 4: Read the path rows

Each row in the table is a unique path observed in the period, displayed as a sequence of numbered chips. Reading from left to right gives you the chronological order.

Three columns:

• Visitors — unique people who went through this exact path
• Conversions — total conversion events from this path
• Revenue — attributed revenue when payment integrations are connected

Sort by Conversions to see the highest-volume paths first. That’s where your real funnel structure lives.

Step 5: Read the patterns that matter

Once the table is sorted by Conversions (descending), look for these patterns:

Single-touch top rows (1 social, 1 paid_search, 1 referral) → high-intent traffic that converts on first arrival. These are your best paid-acquisition opportunities, double down where the CPA is good.

Two-touch paths with the same closer (1 social → 2 paid_search, 1 referral → 2 paid_search) → the first channel is the discovery driver, the second is the closer. Paid search is doing a lot of “closing” work here; cutting it without thinking would crater your overall conversion rate, even though it’s not the original source.

Repeat-channel paths (1 social → 2 social → 3 social, with Collapse OFF) → social is doing both discovery and reinforcement. The channel needs frequency in your bidding strategy, that’s a multi-impression brand-building motion, not a one-click direct-response motion.

Paths ending in Direct (1 paid_social → 2 organic_search → 3 Direct) → classic awareness → consideration → close pattern. The earlier channels worked: brand recall closed the deal. Don’t kill paid_social just because it’s not in the last position; without it, the whole path wouldn’t exist.

Email assists in the middle (1 social → 2 email → 3 paid_social) → your nurture sequence is working. Email picked up an unconverted social visitor and re-engaged them before they converted via paid social. This is the kind of pattern that justifies investing in lifecycle marketing.

Step 6: Compare paths under different attribution models

Path data is structurally attribution-model-agnostic, the sequence itself doesn’t change when you switch models. But the Visitors, Conversions, and Revenue columns do, because those numbers aggregate per the selected model.

Two useful comparisons:

• Last Touch view — counts conversions where the last touch in the path was the closer. Useful for understanding what closes.
• Linear or Position-Based view — splits credit across every touch in the path. Useful for understanding total contribution, including assist value.

For deep detail on each model, see Attribution models overview.

Step 7: Export and act

Typical follow-up actions teams take after a Paths dashboard session:

• Budget defence — if you’re under pressure to cut paid social because it’s not Last Touch, export the Paths data and show how often it appears in winning multi-touch sequences. The assist value is real and quantifiable.
• Retargeting design — for paths where Direct closes, set up retargeting on the discovery channels (paid social, paid search) so brand awareness has somewhere to land
• Nurture sequence redesign — paths where email middle-assists tell you which segments respond to email cadence; build sequences that mirror those paths
• Channel kill / keep decisions — channels that never appear in any winning path can be cut without revenue impact (rare, but worth checking quarterly)
• Content sequence planning — Page tab paths show the canonical “browsing journey” for your converters; use that to design internal linking, blog series, and CTA placement

When to use Paths vs Traffic

Quick reference:

• Traffic dashboard — “Which channels drive conversions?” Budget allocation, channel-mix comparisons.
• Paths dashboard — “What sequence of channels do my converters go through?” Multi-touch attribution defence, assist-channel decisions, nurture design.

The two work together: Traffic tells you which channel closes, Paths tells you which channels assisted along the way. Most marketing-mix decisions need both views.

What’s next

• See channel-level conversion summaries: Traffic dashboard
• See landing page performance: Content dashboard
• See where converters live: Locations dashboard
• See device-level conversion: Devices dashboard
• Pick the right attribution model for your reporting: Attribution models overview