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Account Profile insights

Last update: Wed Nov 27 2024 00:00:00 GMT+0000 (Coordinated Universal Time)

CREATED FOR:

  • Developer
  • User

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 51黑料不打烊 Real-Time CDP 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;

Customers per Account Overview customers-per-account-overview

NOTE
The Customers per Account Overview chart includes three drill-through insights: Customers per Account Detail, Opportunities per Account Overview, and Opportunities per Account Detail. These drill-throughs provide more granular insights, breaking down customer and opportunity counts by categories (such as direct and indirect customers) and ranges (like customer and opportunity count bands). These charts are unaffected by any global date filters you may have set.

Questions answered by this insight:

  • What is the distribution of accounts based on whether they have direct or indirect customers?
Select to reveal the SQL that generates this insight
code language-sql 
WITH LatestDate AS (SELECT MAX(inserted_date) AS max_inserted_date FROM adwh_b2b_account_person_association),
     CategorizedData AS (
         SELECT CASE
                    WHEN is_direct = 'true' AND person_count = 0 THEN 'Accounts without Direct Customers'
                    WHEN is_direct = 'false' AND person_count = 0 THEN 'Accounts without Indirect Customers'
                    WHEN is_direct = 'true' AND person_count > 0 THEN 'Accounts with Direct Customers'
                    WHEN is_direct = 'false' AND person_count > 0 THEN 'Accounts with Indirect Customers'
                END AS Account_Category,
                account_count
         FROM adwh_b2b_account_person_association
         WHERE inserted_date = (SELECT max_inserted_date FROM LatestDate)
     ),
     AggregatedData AS (
         SELECT Account_Category, SUM(account_count) AS Accounts
         FROM CategorizedData
         GROUP BY Account_Category
     ),
     AllCategories AS (
         SELECT 'Accounts without Direct Customers' AS Account_Category
         UNION ALL SELECT 'Accounts without Indirect Customers'
         UNION ALL SELECT 'Accounts with Direct Customers'
         UNION ALL SELECT 'Accounts with Indirect Customers'
     )
SELECT ac.Account_Category AS Account_Category, COALESCE(ad.Accounts, 0) AS Accounts
FROM AllCategories ac
LEFT JOIN AggregatedData ad ON ac.Account_Category = ad.Account_Category
ORDER BY ac.Account_Category;

Customers per Account Detail customers-per-account-detail

NOTE
This insight is unaffected by global date filters.

Questions answered by this insight:

  • How many accounts have different ranges of direct or indirect customers?
Select to reveal the SQL that generates this insight
code language-sql 
WITH customer_ranges AS (
    SELECT 'Direct Customer' AS customer_type, '1-10 Customers' AS person_range
    UNION ALL
    SELECT 'Direct Customer', '11-100 Customers'
    UNION ALL
    SELECT 'Direct Customer', '101-1000 Customers'
    UNION ALL
    SELECT 'Direct Customer', '1000+ Customers'
    UNION ALL
    SELECT 'Indirect Customer', '1-10 Customers'
    UNION ALL
    SELECT 'Indirect Customer', '11-100 Customers'
    UNION ALL
    SELECT 'Indirect Customer', '101-1000 Customers'
    UNION ALL
    SELECT 'Indirect Customer', '1000+ Customers'
)
SELECT
    cr.customer_type,
    cr.person_range,
    COALESCE(SUM(ap.account_count), 0) AS Accounts
FROM customer_ranges cr
LEFT JOIN (
    SELECT
        CASE
            WHEN is_direct = 'true' THEN 'Direct Customer'
            ELSE 'Indirect Customer'
        END AS customer_type,
        CASE
            WHEN person_count BETWEEN 1 AND 10 THEN '1-10 Customers'
            WHEN person_count BETWEEN 11 AND 100 THEN '11-100 Customers'
            WHEN person_count BETWEEN 101 AND 1000 THEN '101-1000 Customers'
            WHEN person_count > 1000 THEN '1000+ Customers'
        END AS person_range,
        SUM(account_count) AS account_count
    FROM adwh_b2b_account_person_association
    WHERE inserted_date = (SELECT MAX(inserted_date) FROM adwh_b2b_account_person_association)
    GROUP BY
        CASE
            WHEN is_direct = 'true' THEN 'Direct Customer'
            ELSE 'Indirect Customer'
        END,
        CASE
            WHEN person_count BETWEEN 1 AND 10 THEN '1-10 Customers'
            WHEN person_count BETWEEN 11 AND 100 THEN '11-100 Customers'
            WHEN person_count BETWEEN 101 AND 1000 THEN '101-1000 Customers'
            WHEN person_count > 1000 THEN '1000+ Customers'
        END
) ap ON cr.customer_type = ap.customer_type AND cr.person_range = ap.person_range
GROUP BY cr.customer_type, cr.person_range
ORDER BY cr.customer_type,
    CASE cr.person_range
        WHEN '1-10 Customers' THEN 1
        WHEN '11-100 Customers' THEN 2
        WHEN '101-1000 Customers' THEN 3
        WHEN '1000+ Customers' THEN 4
    END;

Opportunities per Account Overview opportunities-per-account-overview

NOTE
This insight is unaffected by global date filters.

Questions answered by this insight:

  • What is the distribution of accounts based on whether they have associated opportunities?
Select to reveal the SQL that generates this insight
code language-sql 
WITH LatestDate AS (
    SELECT MAX(inserted_date) AS max_inserted_date
    FROM adwh_b2b_account_opportunity_association
),
CategorizedData AS (
    SELECT
        CASE
            WHEN opportunity_count = 0 THEN 'Accounts without Opportunities'
            WHEN opportunity_count > 0 THEN 'Accounts with Opportunities'
        END AS Opportunity_Category,
        account_count
    FROM adwh_b2b_account_opportunity_association
    WHERE inserted_date = (SELECT max_inserted_date FROM LatestDate)
),
AggregatedData AS (
    SELECT
        Opportunity_Category,
        SUM(account_count) AS Accounts
    FROM CategorizedData
    GROUP BY Opportunity_Category
),
AllCategories AS (
    SELECT 'Accounts without Opportunities' AS Opportunity_Category
    UNION ALL
    SELECT 'Accounts with Opportunities'
)
SELECT
    ac.Opportunity_Category AS Opportunity_Category,
    COALESCE(ad.Accounts, 0) AS Accounts
FROM AllCategories ac
LEFT JOIN AggregatedData ad
    ON ac.Opportunity_Category = ad.Opportunity_Category
ORDER BY ac.Opportunity_Category;

Opportunities per Account Detail opportunities-per-account-detail

NOTE
This insight is unaffected by global date filters.

Questions answered by this insight:

  • How many accounts have different ranges of associated opportunities?
Select to reveal the SQL that generates this insight
code language-sql 
WITH opportunity_ranges AS (
    SELECT '1-10 Opportunities' AS opportunity_range
    UNION ALL
    SELECT '11-50 Opportunities'
    UNION ALL
    SELECT '51-100 Opportunities'
    UNION ALL
    SELECT '100+ Opportunities'
)
SELECT opportunity_ranges.opportunity_range AS OPPORTUNITIES,
       COALESCE(SUM(accounts.total_accounts), 0) AS ACCOUNTS
FROM opportunity_ranges
LEFT JOIN (
    SELECT
        CASE
            WHEN opportunity_count BETWEEN 1 AND 10 THEN '1-10 Opportunities'
            WHEN opportunity_count BETWEEN 11 AND 50 THEN '11-50 Opportunities'
            WHEN opportunity_count BETWEEN 51 AND 100 THEN '51-100 Opportunities'
            WHEN opportunity_count > 100 THEN '100+ Opportunities'
        END AS opportunity_range,
        SUM(account_count) AS total_accounts
    FROM adwh_b2b_account_opportunity_association
    WHERE inserted_date = (SELECT MAX(inserted_date) FROM adwh_b2b_account_opportunity_association)
      AND opportunity_count > 0
    GROUP BY
        CASE
            WHEN opportunity_count BETWEEN 1 AND 10 THEN '1-10 Opportunities'
            WHEN opportunity_count BETWEEN 11 AND 50 THEN '11-50 Opportunities'
            WHEN opportunity_count BETWEEN 51 AND 100 THEN '51-100 Opportunities'
            WHEN opportunity_count > 100 THEN '100+ Opportunities'
        END
) AS accounts ON opportunity_ranges.opportunity_range = accounts.opportunity_range
GROUP BY opportunity_ranges.opportunity_range
ORDER BY CASE opportunity_ranges.opportunity_range
            WHEN '1-10 Opportunities' THEN 1
            WHEN '11-50 Opportunities' THEN 2
            WHEN '51-100 Opportunities' THEN 3
            WHEN '100+ Opportunities' THEN 4
        END;

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. Refer to the Query Pro Mode overview to learn how to generate custom insights with SQL.

You can also read and understand the SQL that generates insights for the Profiles, Audiences, and Destinations dashboards.

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