to Getting More Quality Leads
Growth Hacking: finding customers where no one is looking
Predictive scoring for any company (not just the Fortune 500)
where no one
Growth hackers are a hybrid of marketer and coder, one
who looks at the traditional question of “How do I get
customers for my product?” and answers with A/B tests,
landing pages, viral factor, email deliverability, and Open
Graph. On top of this, they layer the discipline of direct
marketing, with its emphasis on quantitative measurement, scenario modeling via
spreadsheets, and a lot of database queries. If a startup is pre-product/market fit,
growth hackers can make sure virality is embedded at the core of a product. After
product/market fit, they can help run up the score on what’s already working.
This isn’t just a single role – the entire marketing
team is being disrupted. Rather than a VP of
Marketing with a bunch of non-technical marketers
reporting to them, instead growth hackers are
engineers leading teams of engineers. The process
of integrating and optimizing your product to a
big platform requires a blurring of lines between
marketing, product, and engineering, so that they
work together to make the product market itself.
Projects like email deliverability, page-load times,
and Facebook sign-in are no longer technical
or design decisions – instead they are offensive
weapons to win in the market.
The rise of the
The new job title of
is integrating itself
into Silicon Valley’s
that coding and
technical chops are
now an essential
part of being a great
These skills are invaluable and can change the trajectory
of a new product. For the first time ever, it’s possible for
new products to go from zero to 10s of millions users
in just a few years. Great examples include Pinterest,
Zynga, Groupon, Instagram, Dropbox. New products with
incredible traction emerge every week. These products,
with millions of users, are built on top of new, open
platforms that in turn have hundreds of millions of users
– Facebook and Apple in particular. Whereas the web in
1995 consisted of a mere 16 million users on dialup, today
over 2 billion people access the internet. On top of these
unprecedented numbers, consumers use super-viral communication platforms that
rapidly speed up the proliferation of new products – not only is the market bigger,
but it moves faster too.
Before this era, the discipline of marketing relied on the only communication
channels that could reach 10s of millions of people – newspaper, TV, conferences,
and channels like retail stores. To talk to these communication channels, you used
people – advertising agencies, PR, keynote speeches, and business development.
Today, the traditional communication channels are fragmented and passe. The
fastest way to spread your product is by distributing it on a platform using APIs, not
MBAs. Business development is now API-centric, not people-centric.
Whereas PR and press used to be the drivers of customer acquisition, instead it’s
now a lagging indicator that your Facebook integration is working. The role of the
VP of Marketing, long thought to be a non-technical role, is rapidly fading and in its
place, a new breed of marketer/coder hybrids have emerged.
The stakes are
huge because of
Let’s use case of Airbnb to illustrate this mindset. First,
recall The Law of Shitty Clickthroughs:
Over time, all marketing strategies result in shitty
The converse of this law is that if you are first-to-market, or just as well, first-
to-marketing-channel, you can get strong clickthrough and conversion
rates because of novelty and lack of competition. This presents a compelling
opportunity for a growth team that knows what they are doing – they can do
a reasonably difficult integration into a big platform and expect to achieve an
advantage early on.
Airbnb does just this, with a remarkable Craigslist integration. They’ve picked a
platform with 10s of millions of users where relatively few automated tools exist,
and have created a great experience to share your Airbnb listing. It’s integrated
simply and deeply into the product, and is one of the most impressive ad-hoc
integrations I’ve seen in years. Certainly a traditional marketer would not have
come up with this, or known it was even possible – instead it’d take a marketing-
minded engineer to dissect the product and build an integration this smooth.
a case study
Here’s how it works at a UI level, and then we’ll dissect the technology bits:
(This screenshots are courtesy of Luke Bornheimer and his wonderful answer on Quora)
Looks simple, right? The impressive part is that this is done with no public Craigslist
API! It turns out, you have to look closely and carefully at Craigslist in order to
accomplish an integration like this. Note that it’s 100X easier for me to reverse
engineer something that’s already working versus coming up with the reference
implementation – and for this reason, I’m super impressed with this integration.
The first thing you have to do is to look at how Craigslist
allows users to post to the site. Without an API, you have
to write a script that can scrape Craigslist and interact with
its forms, to pre-fill all the information you want.
The first thing you can notice from playing around with
Craigslist is that when you go to post something, you get a unique URL where
all your information is saved. So if you go to https://post.craigslist.org you’ll
get redirected to a different URL that looks like https://post.craigslist.org/k/
HLjRsQyQ4RGu6gFwMi3iXg/StmM3?s=type. It turns out that this URL is unique,
and all information that goes into this listing is associated to this URL and not to
your Craigslist cookie. This is different than the way that most sites do it, where a
bunch of information is saved in a cookie and/or server-
side and then pulled out. This unique way of associating
your Craigslist data and the URL means that you can
build a bot that visits Craigslist, gets a unique URL, fills
in the listing info, and then passes the URL to the user
to take the final step of publishing. That becomes the
foundation for the integration.
At the same time, the bot needs to know information to
deal with all the forms – beyond filling out the Craigslist
category, which is simple, you also need to know which
geographical region to select. For that, you’d have to visit
every Craigslist in every market they serve, and scrape
the names and codes for every region. Luckily, you can
start with the links in the Craigslist sidepanel – there’s
100s of different versions of Craigslist, it turns out.
“Post to Craigslist”
If you dig around a little bit you find that certain geographical markets are more
detailed than others. In some, like the SF Bay Area, there’s subareas (south
bay, peninsula, etc.) and neighborhoods (bernal, pacific heights) whereas in
other markets there’s only subareas, or there’s just the market. So you’d have to
incorporate all of that into your interface.
Then there’s the problem of the listing itself – by default, Craigslist works by giving
you an anonymous email address which you use to communicate to potential
customers. If you want to drive them to your site, you’d have to notice that you can
turn off showing an email, and just provide the “Contact me here” link instead. Or,
you could potentially fill a special email address like email@example.com that
automatically directs inquiries to the right person, which can be done using services
like Mailgun or Sendgrid.
Finally, you’ll want the listing to look good – it turns out Craigslist only supports a
limited amount of HTML, so you’ll need to work to make your listings work well
within those constraints.
Completing the integration is only the beginning – once it’s up, you’d have to
optimize it. What’s the completion % once sometime starts sharing their listing out to
Craigslist? How can you change the flow, the call to action, the steps in the form, to
increase this %? And similarly, when people land from Craigslist, how do you make
sure they are likely to complete a transaction? Do they need special messaging?
Tracking all of this requires additional work with click-tracking with unique URLs,
1×1 GIFs on the Craigslist listing, and many more details.
Long story short, this kind of integration is not trivial. There’s many little details to
notice, and I wouldn’t be surprised if the initial integration took some very smart
people a lot of time to perfect.
Let’s be honest, a traditional marketer would not even
be close to imagining the integration above – there’s too
many technical details needed for it to happen. As a result,
it could only have come out of the mind of an engineer
tasked with the problem of acquiring more users from
Craigslist. Who knows how much value Airbnb is getting
from this integration, but in my book, it’s damn impressive.
It taps into a low-competition, huge-volume marketing
channel, and builds a marketing function deeply into the product. Best of all, it’s a
win-win for everyone involved – both the people renting out their places by tapping
into pre-built demand, and for renters, who see much nicer listings with better
photos and descriptions.
This is just a case study, but with this type of integration, a new product is able to
compete not just on features, but on distribution strategy as well. In this way, two
identical products can have 100X different outcomes, just based on how well they
integrate into Craigslist/Twitter/Facebook. It’s an amazing time, and a new breed of
creative, technical marketers are emerging. Watch this trend.
(not just the
When your sales and marketing teams know exactly which prospects to invest their
time and energy into, they gain a distinct competitive advantage. They can operate
more efficiently and capture more of the revenue opportunity.
You may already be scoring your leads. This manages to separate your “low
probability” leads from “hot leads.” Not bad. It’s a good start. But new tools and
resources can give you the ability to uncover solid prospects.
This process is known by many names such as predictive lead scoring and
determining your Ideal Customer Profile (ICP). To optimize leads using in-house
talent, first do a deep dive on your customer data. Follow these steps to vet the
leads that are most likely to buy.
yy Pull all your customer data.
yy Decide which of the best customers you want to “clone.” This means
eliminating customers that are outside of your desired range with respect to
metrics such as revenue, profit, or timeliness of payment.
yy Look for patterns and segment with regard to industries, company size, or
any other similarities you can find to build an ICP.
yy Then dive into paid or internal data sources to best match companies to
yy Prioritize your leads based on how similar they are to your ICP.
yy If you can, have data scientists do a deeper dive to find other similarities
between your customers or look for online buying signals to prioritize the
If you don’t have the internal resources to do all of this then we would
certainly encourage you to try our tool, LeadCrunch, which does all of this
for you using artificial intelligence. Your first 100 leads are FREE and our
plans start at just $250/month.
www.LeadCrunch.com // www.Englue.com
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