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Tasuki Keifu: Initial SEO and Analytics Plan

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Initial SEO and Traffic Measurement Plan

1. Purpose

This document recorded the SEO and analytics direction agreed for tasuki-keifu / 襷の系譜 at the time, so implementation could proceed without repeatedly reopening the same decisions. It is a historical first-phase plan. A later V2 plan changed the page-priority assessment after more competition and school data had been imported.

2. Positioning

The site used two complementary descriptions. For visitors, its brand was 襷の系譜. For search engines, its subject was an ekiden database. A visitor should find a recognizable data site; a crawler should understand structured entities such as athletes, schools, competitions, and records.

3. SEO Goal

The primary goal was more visits from search. The proposed first-phase success measure was a gradual increase in visits from searches for athlete names. Supporting goals were stable indexing of more athlete profiles, long-tail traffic as the dataset grew, and clearer understanding by AI search or summary systems.

4. First-Phase Scope

Athlete Profiles as the Initial Focus

At the time of this plan, athlete profiles were judged the most mature and consistently growing page group. The team wanted ordinary athlete-name searches to lead into the site before expanding the race or school strategy. This was the original assessment; the later V2 document revised priorities in light of the repository's stronger race and school assets.

Search Terms

The first focus was a person's name alone, for example 黒田朝日, 平林清澄, or 吉居駿恭. The plan did not create large numbers of combination-keyword pages for every person, school, race, and result. One athlete should have one authoritative profile page, which could also answer more detailed queries.

Indexing

The initial decision was to allow crawlers to access and index all athlete pages without a completeness threshold, aiming to capture long-tail name searches. Very weak pages could be assessed separately later. This is a historical decision; V2 subsequently proposed quality tiers instead.

5. Language Strategy

Japanese was the first SEO priority because athlete, competition, and school names naturally appear in Japanese, as did the target audience's searches. The ja route was the main indexing entry. Chinese and English routes could remain, but the first phase would not spread core SEO effort evenly across three languages.

6. What an Athlete Page Should Answer

An athlete page combined identity, affiliation and history, and race results. It was positioned as an understandable athlete profile and record archive, rather than solely an encyclopedia entry or a results table.

After searching a name, a visitor should quickly learn who the athlete is, where they belong or have belonged, which races they have run, and what their records and results show.

Titles

The proposed pattern was name + data terms + brand, such as:

  • 黒田朝日の所属・記録・箱根駅伝成績 | 駅伝データベース 襷の系譜
  • 平林清澄の所属・記録・大会成績 | 駅伝データベース 襷の系譜

The name preserves relevance for a name-only search; the additional terms explain what the page offers.

Descriptions

The first half of a meta description should identify the athlete. The second should mention available affiliation, PB, race records, event relationships, and data sources where those facts are actually present.

7. Success Signals

The most important proposed metric was search visits originating from athlete-name queries. Supporting measures included the number of indexed athlete pages, impressions, clicks, click-through rate, queries bringing traffic, and profiles most often used as search landing pages.

If the strategy worked, more profiles would receive impressions, name-only searches would produce visits, and mid-tier or long-tail athletes would begin to generate steady search traffic. These were expectations, not observed results in this plan.

8. Search Platforms

The first phase included Google Search Console and Bing Webmaster Tools. Google was essential; Bing desktop search in Japan was judged worth monitoring from the start.

9. Analytics Goal

Traffic volume alone would not explain whether the product helped users. Measurement needed to answer how visitors found the site and what they did after arriving.

10. Tools

The selected first-phase tools were GA4 for events and behavior, including searches, clicks, profile entries, and relationship navigation, and Cloudflare Web Analytics for basic traffic and lightweight performance signals. The latter was a low-effort complementary view.

11. First Event Set

The plan favored a focused group of high-signal events: search, filtering, detail-page entry, internal relationship navigation, and outbound source clicks.

EventQuestion it helps answer
home_search_submitWhat do visitors first try to find? Is home search an important entry?
players_search_submitWhich athletes are searched within the site, and does that differ from external search traffic?
players_filter_applyDo visitors explore by school, status, or type?
player_profile_viewWhich profiles attract visits or become landing pages?
competition_detail_viewDo visitors move from an athlete to a race?
organization_detail_viewDo visitors move from an athlete to a school or organization?
player_to_competition_clickIs the athlete-to-race path useful?
player_to_organization_clickIs the athlete-to-school or organization path valuable?
player_to_related_player_clickDo related-athlete links prompt further exploration?
source_outbound_clickDo visitors check original sources, and which pages act as reference material?

Lower-priority events included race and organization search submissions, language switches, pagination, every button click, and fine-grained filter changes. The objective was decision-useful data rather than a complete clickstream.

12. Proposed Implementation Order

SEO and analytics were to be implemented together. The first SEO infrastructure covered metadataBase, page-level metadata, canonical URLs, hreflang, robots.txt, and sitemap.xml. Search-platform integration covered Google Search Console and Bing Webmaster Tools. Analytics included GA4 and Cloudflare Web Analytics, followed by the first batch of search, filter, detail, relationship, and source-click events.

13. Explicit First-Phase Exclusions

The plan did not require combination-keyword landing pages, an initial human-defined high/low-quality indexing split, equal SEO investment in three languages, or heavy instrumentation of every click. Race pages, school and organization pages, and aggregation pages were possible later expansion areas once athlete-page search began to grow. Examples included a specific race edition, a school's participation history, results for a period, or PB rankings for an event.

Tasuki Keifu: Initial SEO and Analytics Plan | Xuhuan / Gelatoni