[B2B Edition]{class="badge informative"} [B2P Edition]{class="badge informative"}
Account Profile insights
Last update: Wed May 01 2024 00:00:00 GMT+0000 (Coordinated Universal Time)
Account profiles are used to consolidate account information from various sources, including multiple marketing channels and organizational systems. This unified view enables a comprehensive understanding of customer accounts, enhancing B2B marketing campaigns. The insights derived from the analysis of your data model make your Adobe Real-time Customer Data Platform B2B data more accessible, understandable, and impactful for decision-making.
With access to the SQL that powers your insights, you can better understand your B2B data and generate your own highly customized reusable insights to further explore your customer account information. Transform your raw data into new actionable insights by using the existing Real-Time CDP data model SQL as inspiration to create queries for your unique business needs.
The following insights are all available for you to use as part of the Account Profiles dashboard or a custom dashboard. See the customization overview for instructions on how to customize your dashboard or create and edit new widgets in the widget library and user-defined dashboard.
Account profiles added account-profiles-added
Questions answered by this insight:
- How many account profiles have been added over a given period?
Select to reveal the SQL that generates this insight
code language-sql |
WITH accounts_by_mm_dd AS
(
SELECT d.date_key,
COALESCE(Sum(a.counts), 0) AS account_counts
FROM adwh_b2b_date d
LEFT JOIN adwh_fact_account a
ON d.date_key = a.accounts_created_date
WHERE d.date_key BETWEEN Upper(COALESCE('$START_DATE', '')) AND Upper(COALESCE('$END_DATE', ''))
GROUP BY d.date_key)
SELECT date_key,
account_counts
FROM accounts_by_mm_dd
ORDER BY date_key limit 5000;
|
New accounts by industry accounts-by-industry
Questions answered by this insight:
- What are the top five industries that the account profiles belong to?
Select to reveal the SQL that generates this insight
code language-sql |
WITH rankedindustries AS
(
SELECT i.industry,
Sum(f.counts) AS total_accounts,
Row_number() OVER (ORDER BY Sum(f.counts) DESC) AS industry_rank
FROM adwh_fact_account f
INNER JOIN adwh_dim_industry i
ON f.industry_id = i.industry_id
WHERE f.accounts_created_date BETWEEN Upper(COALESCE('$START_DATE', '')) AND Upper(COALESCE('$END_DATE', ''))
GROUP BY i.industry )
SELECT
CASE
WHEN industry_rank <= 5 THEN industry
ELSE 'Others'
END AS industry_group,
Sum(total_accounts) AS total_accounts
FROM rankedindustries
GROUP BY
CASE
WHEN industry_rank <= 5 THEN industry
ELSE 'Others'
END
ORDER BY total_accounts DESC limit 5000;
|
New accounts by type accounts-by-type
Questions answered by this insight:
- What is the count of accounts by their type?
Select to reveal the SQL that generates this insight
code language-sql |
SELECT t.account_type,
Sum(f.counts) AS account_count
FROM adwh_fact_account f
JOIN adwh_dim_account_type t
ON f.account_type_id = t.account_type_id
WHERE accounts_created_date BETWEEN Upper(Coalesce('$START_DATE', '')) AND
Upper(
Coalesce('$END_DATE', ''))
GROUP BY t.account_type
LIMIT 5000;
|
Opportunities added opportunities-added
Questions answered by this insight:
- How many opportunities have been added over a given period?
Select to reveal the SQL that generates this insight
code language-sql |
SELECT d.date_key,
Coalesce(Sum(o.counts), 0) AS opportunity_counts
FROM adwh_b2b_date d
LEFT JOIN adwh_fact_opportunity o
ON d.date_key = o.opportunities_created_date
WHERE d.date_key BETWEEN Upper(Coalesce('$START_DATE', '')) AND
Upper(Coalesce('$END_DATE', ''))
GROUP BY d.date_key
ORDER BY d.date_key
LIMIT 5000;
|
New opportunities by person role opportunities-by-person-role
Questions answered by this insight:
- What is the relative size and count of the various roles in an opportunity?
Select to reveal the SQL that generates this insight
code language-sql |
SELECT p.person_role,
Sum(f.counts) AS opportunity_counts
FROM adwh_fact_opportunity_person f
JOIN adwh_dim_person_role p
ON f.person_role_id = p.person_role_id
WHERE f.opportunity_person_created_date BETWEEN
Upper(Coalesce('$START_DATE', '')) AND Upper(Coalesce('$END_DATE', ''))
GROUP BY p.person_role
LIMIT 5000;
|
New opportunities by revenue opportunities-by-revenue
Questions answered by this insight:
- What are the top 20 opportunities ranked by their revenue (in USD)?
Select to reveal the SQL that generates this insight
code language-sql |
WITH ranked_opportunities AS
(
SELECT n.opportunity_name,
a.expected_revenue,
t.source_type,
Row_number() OVER (ORDER BY a.expected_revenue DESC) AS rank
FROM adwh_opportunity_amount a
INNER JOIN adwh_dim_opportunity_name n
ON a.name_id = n.name_id
INNER JOIN adwh_dim_opportunity_source_type t
ON n.source_type_id = t.source_type_id
WHERE a.opportunity_created_date BETWEEN Upper(COALESCE('$START_DATE', '')) AND Upper(COALESCE('$END_DATE', ''))
AND a.isclosed='false' )
SELECT
CASE
WHEN rank <= 20 THEN opportunity_name
ELSE 'Others'
END AS opportunity_name,
Sum(expected_revenue) AS total_expected_revenue
FROM ranked_opportunities
GROUP BY
CASE
WHEN rank <= 20 THEN opportunity_name
ELSE 'Others'
END,
source_type
ORDER BY total_expected_revenue DESC limit 5000;
|
New opportunities by status & stage opportunities-by-status-and-stage
Questions answered by this insight:
- What open opportunities are there and at which stage of the sales or marketing funnel are they?
- What closed opportunities are there and at which stage of the sales or marketing funnel are they?
Select to reveal the SQL that generates this insight
code language-sql |
WITH opportunities_by_isclosed AS
(
SELECT f.isclosed,
Sum(f.counts) AS opportunity_counts,
COALESCE(s.stage, 'null') AS stage
FROM adwh_fact_opportunity f
JOIN adwh_dim_opportunity_stage s
ON f.stage_id = s.stage_id
WHERE opportunities_created_date BETWEEN Upper(COALESCE('$START_DATE', '')) AND Upper(COALESCE('$END_DATE', ''))
GROUP BY f.isclosed,
s.stage)
SELECT
CASE
WHEN isclosed='true' THEN 'Closed'
ELSE 'Open'
END AS opportunity_closed,
stage,
opportunity_counts
FROM opportunities_by_isclosed limit 5000;
|
New opportunities won opportunities-won
Questions answered by this insight:
- What is the count of opportunities that have been successfully closed or finalized?
Select to reveal the SQL that generates this insight
code language-sql |
WITH opportunities_by_iswon AS
(
SELECT iswon,
Sum(counts) AS opportunity_counts
FROM adwh_fact_opportunity
WHERE opportunities_created_date BETWEEN Upper(COALESCE('$START_DATE', '')) AND Upper(COALESCE('$END_DATE', ''))
GROUP BY iswon)
SELECT
CASE
WHEN iswon ='true' THEN 'True'
ELSE 'False'
END AS opportunity_won,
opportunity_counts
FROM opportunities_by_iswon limit 5000;
|
Opportunities won (line graph) opportunities-won-line-graph
Questions answered by this insight:
- How many opportunities have been successfully closed or finalized (won) over a given period?
Select to reveal the SQL that generates this insight
code language-sql |
WITH opportunities_won_counts AS
(
SELECT opportunities_created_date,
Sum(counts) AS opportunities_counts
FROM adwh_fact_opportunity
WHERE iswon='true'
AND opportunities_created_date BETWEEN Upper(COALESCE('$START_DATE', '')) AND Upper(COALESCE('$END_DATE', ''))
GROUP BY opportunities_created_date)
SELECT d.date_key,
COALESCE(o.opportunities_counts, 0) AS opportunity_won_counts
FROM adwh_b2b_date d
LEFT JOIN opportunities_won_counts o
ON d.date_key = o.opportunities_created_date
WHERE d.date_key BETWEEN Upper(COALESCE('$START_DATE', '')) AND Upper(COALESCE('$END_DATE', ''))
ORDER BY d.date_key limit 5000;
|
Next steps
By reading this document, you now understand the SQL that generates account profile dashboard insights and what common questions this analysis solves. You can now edit and iterate on the SQL to generate your own insights.
You can also read and understand the SQL that generates insights for the Profiles, Audiences, and Destinations dashboards.