How to Use the Automata Market Intelligence APIs for Market Research on Newly Funded Startups

Whether you are an investor or running a startup, understanding the fundraising landscape is essential. You are either competing for dollars or competing for a piece of the best talent and ideas. Crunchbase is hands-down the best resource for understanding the startup fundraising landscape and its API can be a great way for analysts and founders to automate the discovery and analysis of fundraising trends. You can find the Crunchbase API on RapidAPI to start automating your due diligence or competitive analysis tasks.

Since new companies are generally unknown, it’s often useful to look at other companies in a similar space that are already testing the market, providing value, and generating revenue. The Market Intelligence API by Automata can help with this discovery by analyzing the content on webpages and delivering Company Lookalikes.

Check out the Github repository to see this whole process in detail.

How to Find Newly Funded Companies with the Crunchbase API

The new seed rounds that were announced today can be found using the Crunchbase API with this function written in Python. The input parameters are your RapidAPI key and the number of companies you’d like to analyze

def get_todays_funding_announcements(key, num):
    headers = {
        'x-rapidapi-host': "crunchbase-crunchbase-v1.p.rapidapi.com",
        'x-rapidapi-key': key
    }
    
    timestamp = int(datetime.combine(date.today(), datetime.min.time()).timestamp())
    querystring = {"updated_since": timestamp}
    
    url_cb_funding = "https://crunchbase-crunchbase-v1.p.rapidapi.com/funding-rounds"
    response = requests.request("GET", url_cb_funding, headers=headers, params=querystring)
    funding_rounds = [x.get("properties") for x in response.json().get("data").get("items")]
    
    funding_uids = [ x.get("permalink") for x in funding_rounds if x.get("funding_type") == "seed" ]
    url_cb_details = [ url_cb_funding + "/{}".format(x) for x in funding_uids ]
    funded_companies = []
    for url_ in url_cb_details[:num]:
        company_response = requests.request("GET", url_, headers=headers).json()
        r = company_response.get("data").get("relationships")
        o = r.get("funded_organization").get("item").get("properties")
        funded_companies.append(o)
    return [ {
        "website": x.get("homepage_url"), 
        "description": x.get("description") 
    } for x in funded_companies ]

The function first retrieves unique identifiers for the seed rounds that were announced today on Crunchbase. It then loops through the requested number of funding events to get the details of the funded organizations. It returns an array of objects with the website and description of the funded companies. Note: this function consumes (num + 1) Crunchbase API calls, so choose your parameters carefully.

Related: Build an Automated Sales Pipeline with Crunchbase API

An example of the returned seed-funded companies for April 22, 2020 will look like this:

[
    {
        'website': 'https://www.keepertax.com/', 
        'description': 'Keeper helps 1099 contractors automatically find tax write offs in their bank statements.nnKeeper Tax was founded in 2018 and is headquartered in San Francisco, CA, USA.'
    }, {
        'website': 'https://www.heytimetraveler.com/', 
        'description': 'TimeTraveler is a consumer electronics company that offers hardware and software for virtual reality. It features a technology device and software that leverages smartphones with compact / user-friendly hardware and 360°VR content to deliver immersive VR experiences that take users back in time.nnThe company was founded in 2019 and headquartered in Chicago, Illinois.'
    },
    ...
]

Find Company Lookalikes with the Market Intelligence API by Automata

Now that the newly funded companies have been identified, let’s take a look at some Company Lookalikes with the Market Intelligence API by Automata via RapidAPI (read the full docs). This will give us insight into the markets that were funded today and the potential competitive landscape. We loop through the funded companies and generate a list of Company Lookalikes based on their websites. The inputs to this function are the funded companies from above and your RapidAPI key.

def get_company_lookalikes(funded_company_details, key):
    headers = {
        'x-rapidapi-host': "market-intelligence-by-automata.p.rapidapi.com",
        'x-rapidapi-key': key
    }
    url_automata_similar = "https://market-intelligence-by-automata.p.rapidapi.com/similar"
    
    query_strings = [{"page":"0","link":x.get("website")} for x in funded_company_details]
    
    company_lookalikes = []
    for s in query_strings:
        response = requests.request("GET", url_automata_similar, headers=headers, params=s)
        company_lookalikes.append({
            "input_company": s.get("link"),
            "similar_companies": response.json().get("companies")
        })
    return company_lookalikes

The get_company_lookalikes function returns an array of Company Lookalikes for each of the funded companies. The objects include the Company Lookalike’s website, industry, LinkedIn page, and several other descriptive fields that can be used to analyze the funding landscape. A snippet of the response for our example (keepertax.com, a software to help freelancers keep track of their taxes) is shown here:

[
    {
        'website': 'painless1099.com', 
        'companyName': 'Painless1099', 
        'linkdedin': 'linkedin.com/company/painless1099',
        ...
    }, 
    {
        'website': 'purchasingplatform.com', 
        'companyName': 'Purchasing Platform', 
        'linkedin': 'linkedin.com/company/purchasing-platform',
        ...
    }, {
        'website': 'payable.com', 
        'companyName': 'Payable', 
        'linkedin': 'linkedin.com/company/tiempo-labs',
        ...
    }, {
        'website': 'timbertax.co', 
        'companyName': 'Timber Tax Pc', 
        'LinkedIn': 'linkedin.com/company/timber-tax-pc',
        ...
    }, {
        'website': '1099pro.com', 
        'companyName': '1099 Pro', 
        'linkedin': 'linkedin.com/company/1099-pro',
        ...
    },
    ...
]

The full response includes more fields for each Lookalike, and will also return results for the other funded companies that we found from Crunchbase. Analyzing Company Lookalikes for these new seed-funded startups is a great way to start understanding the types of companies that are being funded, the potential competitive landscape, and the maturity of the market.

Check out the full script on Github and feel free to contact support@byautomata.io with any questions or comments and check out our Market Intelligence suite at byautomata.io.