Clickthrough rate (CTR)
Clickthrough rate (CTR)
The clickthrough rate is calculated by taking the total number of search events that were followed by at least one click event (with a matching searchQueryUid value) divided by the total number of search events.
This article contains SQL queries to create Snowflake dashboard tiles to report on the following metrics:
To learn how you can create custom dashboards in Snowflake and use the queries listed in this section, see Create Snowflake dashboards.
CTR per component
The query in this section creates a Snowflake dashboard tile that reports on the different Coveo services' components.
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Note
A Coveo service component refers to a specific instance exploited by a Coveo service. For example, you can have many components that leverage the Recommendation service:
In this case, the dashboard will report on these three different components. |
The code sample below serves as a base to get the CTR metric for different Coveo components. Copy the query below and paste it in Snowflake. Don’t forget to add the required information, depending on which Coveo service’s component you want to report on.
with aggregated_info as (
select distinct
ins.organization_id,
{COMPONENT},
count(distinct ins.insight_id) as total_searches,
count(distinct case when click_event_id is not null then ins.insight_id else null end) as total_searches_clicks
from COVEO_CORE_MODEL_V001.COMMON.INSIGHTS ins
join COVEO_CORE_MODEL_V001.COMMON.IMPRESSIONS imp on ins.visit_id = imp.visit_id and ins.insight_id = imp.insight_id
where date(start_time) = :daterange
and date(imp.impression_timestamp) = :daterange
and ins.insight_type = '{INSIGHT-TYPE}' -- ('listing', 'search' or 'recommendation')
group by ins.organization_id, {ALIAS_OF_COMPONENT}
)
select organization_id,
{ALIAS_OF_COMPONENT},
(total_searches_clicks / total_searches) * 100 as ctr
from aggregated_info
order by ctr desc
limit 10Where you replace:
-
{INSIGHT-TYPE}with the Coveo service on which you want to report (i.e.,search,listing, orrecommendation). -
{COMPONENT}depending on the service you selected in step 1:Service selected in step 1 Value to replace {COMPONENT}withsearchquery_expressionlistingec_listingrecommendationorigin as recommendation_component -
Occurrences of
{ALIAS_OF_COMPONENT}, depending on the Coveo service you selected in step 1:Service selected in step 1 Value to replace {ALIAS_OF_COMPONENT}withsearchquery_expressionlistingec_listingrecommendationrecommendation_component
Top 10 query expressions
This query creates a Snowflake dashboard tile that displays the top 10 query expressions that generated the highest CTR.
with aggregated_info as (
select distinct
ins.organization_id,
query_expression,
count(distinct ins.insight_id) as total_searches,
count(distinct case when click_event_id is not null then ins.insight_id else null end) as total_searches_clicks
from COVEO_CORE_MODEL_V001.COMMON.INSIGHTS ins
join COVEO_CORE_MODEL_V001.COMMON.IMPRESSIONS imp on ins.visit_id = imp.visit_id and ins.insight_id = imp.insight_id
where date(start_time) = :daterange
and date(imp.impression_timestamp) = :daterange
and ins.insight_type = 'search'
group by ins.organization_id, query_expression
)
select organization_id,
query_expression,
(total_searches_clicks / total_searches) * 100 as ctr
from aggregated_info
order by ctr desc
limit 10When using the default query, your dashboard should look like the following:
The Chart type, Data, and Appearance sections should look like the following. See Using charts for more information.
Top 10 product listing pages
This query creates a Snowflake dashboard tile that displays the path of the top 10 product listing pages that generated the highest CTR.
with aggregated_info as (
select distinct
ins.organization_id,
ec_listing,
count(distinct ins.insight_id) as total_searches,
count(distinct case when click_event_id is not null then ins.insight_id else null end) as total_searches_clicks
from COVEO_CORE_MODEL_V001.COMMON.INSIGHTS ins
join COVEO_CORE_MODEL_V001.COMMON.IMPRESSIONS imp on ins.visit_id = imp.visit_id and ins.insight_id = imp.insight_id
where date(start_time) = :daterange
and date(imp.impression_timestamp) = :daterange
and ins.insight_type = 'listing'
group by ins.organization_id, ec_listing
)
select organization_id,
ec_listing,
(total_searches_clicks / total_searches) * 100 as ctr
from aggregated_info
order by ctr desc
limit 10When using the default query, your dashboard should look like the following:
The Chart type, Data, and Appearance sections should look like the following. See Using charts for more information.
Top 10 recommendation components
This query creates a Snowflake dashboard tile that displays the recommendation components that generated the highest CTR.
with aggregated_info as (
select distinct
ins.organization_id,
origin as recommendation_component,
count(distinct ins.insight_id) as total_searches,
count(distinct case when click_event_id is not null then ins.insight_id else null end) as total_searches_clicks
from COVEO_CORE_MODEL_V001.COMMON.INSIGHTS ins
join COVEO_CORE_MODEL_V001.COMMON.IMPRESSIONS imp on ins.visit_id = imp.visit_id and ins.insight_id = imp.insight_id
where date(start_time) = :daterange
and date(imp.impression_timestamp) = :daterange
and ins.insight_type = 'recommendation'
group by ins.organization_id, recommendation_component
)
select organization_id,
recommendation_component,
(total_searches_clicks / total_searches) * 100 as ctr
from aggregated_info
order by ctr desc
limit 10When using the default query, your dashboard should look like the following:
The Chart type, Data, and Appearance sections should look like the following. See Using charts for more information.
Very useful
Not really
Very useful
Not really