The Process

Step #1: Build hyper-targeted outreach list

How we do it

After a discussion about your ideal target customer segments, our data scientists, full-stack developers, custom workflows and custom ML models identify your ideal clients and build large, hyper-targeted, hyper-enriched lists to use for scalable outreach.
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​Analyse your current clients (if any) with ML models to extract variables that make up your best customers. If you have less than 10-20 customers, we can instead make an educated guess on who make up your best customers and test rapidly to find variables that cause people to engage with our outreach marketing most favourably. What industries, job titles, locations, tech stack, company size - are likely to get us the most sales meetings.
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​Targeted list will contain 10k-100k rows of data, pulled and cross referenced from multiple data sources:
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​- Crunchbase
​- Angel.co
​- LinkedIn
​- UpLead
​- And more
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​Timeframe: ~3 days

How most startups fail this step

Hiring a cheap off-shore agency to build a list, which often turns out to miss important data points and include irrelevant prospects.

Step #2: High-converting sequences

How we do it

We craft the outreach copy, videos and other content to engage our specific target customer segments most effectively.

- Write outreach copy that cuts through the noise by being open, authentic, transparent, sharp and using simple conversational language that is clear and unique.
​- Add video messages that also capture information from leads via a form (VideoAsk).

Timeframe: ~5 days

How most startups fail this step

"Hello. This is what we sell, are you interested in buying from us?"

Step #3: Personalisation at scale

How we do it

We analyse publicly available information on our target prospects (skills, interests etc) and generate copy snippets that get injected into our outreach messages dynamically based on specific data-points.
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​Example:
​ Let's say 100 of our target prospects have negotiation listed as a skill. We could then inject a line of relevant copy into each of our outreach messages for those 100 prospects:
​ "I see you're a quite the negotiator. Take a look at this PDF and if you like what you see, we may have something to negotiate over!"

Your website / landing page can also be dynamically personalised for every prospect that comes to the website.

Timeframe: ~7 days

How most startups fail this step
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​1. High volume / no personalisation.
​2. Low volume / manual personalisation.
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​We do personalisation at scale.

Step #4: Efficiently responding to leads

How we do it

You can respond to leads easily via a dashboard. After the first ~30 responses, we categorise responses and write templated messages to make answering questions and booking sales meeting highly efficient.

Timeframe: Ongoing

How most startups fail this step

Sporadically respond to leads when they have time, manually responding to every message.

Step #5: Book sales calls

How we do it

We track prospect actions and and automatically create follow-up campaigns to ensure that every interested lead is pursued (e.g. if a prospect clicks your Calendly link, but doesn't book a meeting, we automatically follow-up with them - this is easy via email, but we've built custom systems to handle this via LinkedIn).
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​Timeframe: Start to get sales meetings ~14-30 days after the engagement starts.

​How most startups fail this step

Most founders are too busy to nail follow-ups efficiently which results in consistent new sales meetings.

Step #6: Close deals

How we do it

After a significant number of meeting requests start coming in, we'll connect you with a sales mentor that can help dramatically improve your close rate. These mentors have either founded and/or managed large companies, or run large sales teams at huge organisations.

How most startups fail this step

Try to sell based on features.

Step #7: Analyse data

How we do it

Use custom machine-learning models, as well as third party tools to find more companies who are highly similar to the companies that are responding, booking meetings, converting, as well as those who are most profitable.
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​Timeframe: After 50+ engaged responses (but the more data, the better)

How most startups fail this step

Manually review responses and randomly draw patterns between data, if at all.