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IPP Analysis Strategy

A process for creating and finding your “Ideal” partner persona

*We are compiling a database (which will have a frontend for you to access) of custom persona data (names/titles/size/emails...) to suit our partners’ needs. If you’d like us to add yours and share the results, please complete this Airtable form and we’ll share the results with you.

First - things to consider as you start to create your ‘ideal’ agency personas:

  • Start by breaking up the types of partnership the personas will fit under - define:
    “Pure Referral Partner” vs
    “User + Affiliate” vs
    “User + Implementation/Support Partner” vs
    “Pure Support/Implementation Partner”

    • The reason for this is that you will go after affiliates/referral partners who will not be users in a far different manner than you would go after users who you want to convert to referral partners. And those who will be looked to for implementation support (in the way Salesforce partners are) will be treated differently than the above.

  • Make sure you are using data points you can find online to build your personas - not just firmographics, but preferred software brands, known partnerships, LinkedIn profile keywords...

  • What we do not want to do is come up with this entire persona that’s 10 pages long with psychographic details and dozens of indicators… but the majority of those are just not possible to find online.

  • Because you want to use your directory as part of the hook for new partners, organize your personas in the same taxonomy/category/collections as your partner directory. That is, if your directory is organized by agency vertical and type (i.e. B2B, eComm… then marketing, development, design, etc…) then you will want to segment your personas the same way.

  • I recommend leaving out agency size as it’s usually irrelevant.

Here is where you will start when approaching your persona development:

  1. Starting with your current referral partners database:

    1. Sort them

      1. Partner type,

      2. Activity - if known - last referral data or total referrals

    2. Deconstruct who they are, tools they use, services.

      1. Get their URLs

      2. Similartech, wappalyzer, builtwith

      3. Check out the services section of their LinkedIn company profile.

      4. Use the sheet format below to enrich their profiles

    3. Add who your contact is or would be

    4. Find lookalike companies based on those data points

  2. Competitor partner programs:

    1. Search Google for your competitors' brand + “partner directory”.

    2. If that doesn’t produce results, search LinkedIn for “{{competitor_name}} preferred partner” or “{{competitor_name}} partner”, then filter by industry = ‘marketing and advertising’ + ‘management consulting’

    3. IF your competitors do not have a partner program with agencies, look to the next closest successful platform with a successful partner program.

    4. Create a scrape or manually enrich the directory

    5. Enrich

      1. Get their URLs

      2. Similartech, wappalyzer, builtwith

      3. Check out the services section of their linkedin company profile.

  3. Agencies who service your power users:

    1. Call your top users

    2. Ask about their agencies

    3. Ask for intro’s

    4. Start enrichment

  4. Natively-integrated app partners:

    1. Pull out those native apps who are targeting the same customer types as you.

    2. Which of those have partner programs?

    3. Scrape those directories

    4. Enrich

Airtable management

Why Airtable:

  • Automation - you can trigger automations based on rules within each cell of data, like emails, push to CRM, push to another database, or even a PRM.

  • Forms - each base has a form so you can simply share the form with a VA who’s developing your database and not the base itself. You can also create surveys and data capture landing pages that pull right into your base. If you use Formstack or Typeform, they have integrations with Airtable as well.

  • It allows for ‘view’ sharing - you can have contact data in rows, but only share the non-contact-data view with outside organizations or your consultants.

  • Linking records - you can pull in and link to other Airtable bases so you can better-organize and co-manage.

  • Correlation analysis - after you develop a large database of persona’s, you can run pivot-table-like correlations easily within the Airtable base and use those in meetings with your team or to show marketing key data for your persona’s.

Here are the columns we suggest using for your persona details sheet:

  1. Persona name - don’t get all market’y with this - just name them something that makes sense like “Data-Driven B2B Marketing Agency”.

  2. Brief description - short summary of who this persona is.

  3. Type of agency - i.e. marketing, design, development…

  4. Vertical - where they compete - B2B, eCommerce, Retail, Professional services…

  5. Services - ABM, PPC, SMM, API, or CRM integration…

  6. Possible partners - List of the top brands these agencies are likely to partner with.

  7. Target clients - SMB, Mid-Market, Enterprise, Retailers, D2C, SaaS…

  8. Tools they use now - snippets found on their site using various tech lookups.

  9. ‘LinkedIn Specialties’ - actually copy/paste their Specialties from their LinkedIn company profile.

  10. Company LinkedIn profile URL.

Now, we highly-recommend using Airtable so you can sort, share, export, and create forms for the table.

Tab 1 = your definitions

https://airtable.com/shrEt7GYoypaMu9xJ

Tab’s 2… = your data

https://airtable.com/shrI80eXUaoiQxbha

The data points to include:

  1. Agency Name

  2. Agency Description (copy “About” section from their LinkedIn profile)

  3. Potential partnership type (these will be the same for all agencies in this table, but it’s good to have them tagged here)

  4. Type of agency (same list as the IPP definition tab)

  5. Vertical (same list as the IPP definition tab)

  6. Specialties (taken from their LinkedIn company page)

  7. Tools they use now

  8. Current SaaS partners

  9. Target clients

  10. Contact name

  11. Title

  12. LinkedIn URL

  13. Email

How to get the data:

WATCH THIS VIDEO TUTORIAL OF HOW TO USE LINKEDIN + WIZA TO:

  1. Use Sales Nav to find agencies properly using Boolean keywords searches.

  2. Start with “Accounts Filters” then move accounts to leads.

  3. Use Wiza Chrome extension to save those scrapes.

  4. Manage it all in Airtable using our PRM.

  5. And then a co-marketing vs pure partnerships outreach test strategy.

Our Data Stack:

  • Airtable - for enrichment and prm.

  • https://www.scrapestorm.com/ - to customize scrapes.

  • Wiza.co - for enriching sales navigator lists.

  • Gmass.co - For bulk cold email and email validation.

  • LinkedIn Sales Navigator - for the agency filters (see strategy above)

  • Similartech.com - for lists by tech use

  • Builtwith.com - for tech lookups and data sets

  • Wappalyzer.com - for tech lookups and data sets

  • Ocean.io - for lookalike agency data

**The human will be necessary to gran and find the extra details and combine data from multiple sources - we use a team we’ve trained who are proficient in Airtable + Sales Navigator + our data tools.

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