HubSpot as a data source

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1. Add your HubSpot access

1. In the Sources tab, click on the “Add source” button located on the top right of your screen. Then, select the Hubspot option from the list of connectors.
2. Click Next and you’ll be prompted to add your access. Login with a Hubspot account that has Super Admin permissions in order to install the Nekt app into the workspace.
3. The Start Date is the date of the first record you want to sync with.
4. Configure the following optional settings:
   • Enable Leads Stream: Enable to extract leads data (requires HubSpot Pro, Enterprise, or Enterprise Plus)
   • Extract Contact Associations: Enable to extract related entities for contacts
   • Contact Associations List: If enabled above, specify which associations to extract (comma-separated)
   • Extract Contact Property History: Enable to track property changes for contacts
   • Contact Property History Fields: If enabled above, specify which properties to track (comma-separated)
   • Extract Deal Associations: Enable to extract related entities for deals
   • Deal Associations List: If enabled above, specify which associations to extract (comma-separated)
   • Extract Deal Property History: Enable to track property changes for deals
   • Deal Property History Fields: If enabled above, specify which properties to track (comma-separated)
   • Extract Ticket Associations: Enable to extract related entities for tickets
   • Ticket Associations List: If enabled above, specify which associations to extract (comma-separated)
   • Extract Lead Associations: Enable to extract related entities for leads (requires Enable Leads Stream)
   • Lead Associations List: If enabled above, specify which associations to extract (comma-separated)
   Note: Enabling these options will increase extraction time but provide more detailed relationship data.
5. Click Next.

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2. Select your Hubspot streams

1. The next step is letting us know which streams you want to bring. You can select entire groups of streams or only a subset of them.

   Tip: The stream can be found more easily by typing its name.

2. Click Next.

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3. Configure your Hubspot data streams

1. Customize how you want your data to appear in your catalog. Select the desired layer where the data will be placed, a folder to organize it inside the layer, a name for each table (which will effectively contain the fetched data) and the type of sync.

• Layer: choose between the existing layers on your catalog. This is where you will find your new extracted tables as the extraction runs successfully.
• Folder: a folder can be created inside the selected layer to group all tables being created from this new data source.
• Table name: we suggest a name, but feel free to customize it. You have the option to add a prefix to all tables at once and make this process faster!
• Sync Type: depending on the data you are bringing to the lake, you can choose between INCREMENTAL and FULL_TABLE. Read more about Sync Types here.

2. Click Next.

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4. Configure your Hubspot data source

1. Describe your data source for easy identification within your organization. You can inform things like what data it brings, to which team it belongs, etc.
2. To define your Trigger, consider how often you want data to be extracted from this source. This decision usually depends on how frequently you need the new table data updated (every day, once a week, or only at specific times).
3. Optionally, you can define some additional settings (if available).

• Configure Delta Log Retention and determine for how log we should store old states of this table as it gets updated. Read more about this resource here.
• Determine when to execute an Additional Full Sync. This will complement the incremental data extractions, ensuring that your data is completely synchronized with your source every once in a while.

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Check your new source!

1. Click Next to finalize the setup. Once completed, you’ll receive confirmation that your new source is set up!
2. You can view your new source on the Sources page. Now, for you to be able to see it on your Catalog, you have to wait for the pipeline to run. You can now monitor it on the Sources page to see its execution and completion. If needed, manually trigger the pipeline by clicking on the refresh icon. Once executed, your new table will appear in the Catalog section.

If you encounter any issues, reach out to us via Slack, and we’ll gladly assist you!

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Available Streams and Fields

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Common data transformations

SELECT
	-- list the regular columns you want to see in the final table
	id,
	createdat,
	updatedat,
	archived,
	_nekt_sync_at,
	-- list the fields that come inside 'properties' column and you want to have a specific column for
	properties.name,
	properties.price,
	properties.description
FROM
   -- example: "nekt.raw"."hubspot_products"
	"nekt_layer"."table_name"

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Use Cases

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1. Sales Performance Analytics

-- Sales Performance Dashboard
WITH
   deal_metrics AS (
      SELECT
         d.properties.hubspot_owner_id AS hubspot_owner_id,
         o.firstname || ' ' || o.lastname AS owner_name,
         COUNT(*) AS total_deals,
         SUM(
            CAST(NULLIF(d.properties.amount, '') AS DECIMAL(15, 2))
         ) AS total_value,
         AVG(
            CAST(NULLIF(d.properties.amount, '') AS DECIMAL(15, 2))
         ) AS avg_deal_size,
         COUNT(
            CASE
               WHEN d.properties.dealstage = 'closedwon' THEN 1
            END
         ) AS won_deals,
         COUNT(
            CASE
               WHEN d.properties.dealstage = 'closedlost' THEN 1
            END
         ) AS lost_deals
      FROM
         "nekt_raw"."hubspot_deals" d
         LEFT JOIN "nekt_raw"."hubspot_owners" o ON d.properties.hubspot_owner_id = o.id
      WHERE
         CAST(SUBSTRING(d.properties.createdate, 1, 10) AS DATE) >= DATE_ADD ('month', -6, CURRENT_DATE)
      GROUP BY
         d.properties.hubspot_owner_id,
         o.firstname,
         o.lastname
   )
SELECT
   owner_name,
   total_deals,
   total_value,
   avg_deal_size,
   won_deals,
   lost_deals,
   ROUND((won_deals * 100.0 / total_deals), 2) AS win_rate,
   ROUND((total_value / NULLIF(total_deals, 0)), 2) AS avg_deal_value
FROM
   deal_metrics
ORDER BY
   total_value DESC

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2. Customer Journey Analysis

-- Customer Journey Funnel
WITH
   contact_stages AS (
      SELECT
         properties.lifecyclestage,
         COUNT(*) AS contact_count,
         COUNT(
            CASE
               WHEN properties.lifecyclestage IN (
                  'lead',
                  'marketingqualifiedlead',
                  'salesqualifiedlead'
               ) THEN 1
            END
         ) AS qualified_leads,
         COUNT(
            CASE
               WHEN properties.lifecyclestage = 'opportunity' THEN 1
            END
         ) AS opportunities,
         COUNT(
            CASE
               WHEN properties.lifecyclestage = 'customer' THEN 1
            END
         ) AS customers
      FROM
         "nekt_raw"."hubspot_contacts"
      WHERE
         createdat >= DATE_ADD ('month', -12, CURRENT_DATE)
      GROUP BY
         properties.lifecyclestage
   ),
   funnel_metrics AS (
      SELECT
         'Total Contacts' AS stage,
         SUM(contact_count) AS COUNT,
         100.0 AS conversion_rate
      FROM
         contact_stages
      UNION ALL
      SELECT
         'Qualified Leads' AS stage,
         SUM(qualified_leads) AS COUNT,
         ROUND(
            (SUM(qualified_leads) * 100.0 / SUM(contact_count)),
            2
         ) AS conversion_rate
      FROM
         contact_stages
      UNION ALL
      SELECT
         'Opportunities' AS stage,
         SUM(opportunities) AS COUNT,
         ROUND(
            (SUM(opportunities) * 100.0 / SUM(qualified_leads)),
            2
         ) AS conversion_rate
      FROM
         contact_stages
      UNION ALL
      SELECT
         'Customers' AS stage,
         SUM(customers) AS COUNT,
         ROUND((SUM(customers) * 100.0 / SUM(opportunities)), 2) AS conversion_rate
      FROM
         contact_stages
   )
SELECT
   *
FROM
   funnel_metrics
ORDER BY
   COUNT DESC