Growth Hacking – A Secret to read minds and be available when they need
What if you want to grow faster, Like everyone….. ???
Let me tell you, Infinitely increase sales plans, and advertising budgets will not work. You will spend a lot of money, or all the money at once, and the expected effect will not happen.
After a specific time, channels exhaust themselves and cease to be effective, many of them do not scale at all. Therefore, this approach will not exactly lead to explosive growth.
In this article, we will tell you, how to grow at multiple times, what Growth Hacking is, or, in other words, how to hack a company’s growth?
What is this “Growth hacking”?
Growth Hacking translates as cracking the growth of a company or a startup. Growth hacking occurs due to various, mainly marketing initiatives. They are just called hacks.
Growth hacking is a phased generation and testing of hacks that will lead to growth.
At one time, hacks with the Refer a Friend and Get a Bonus referral program or content marketing brought companies 60% growth or revenue of $ 20 million.
Let’s see Some Famous Growth Examples
Before dive deep into the learning of Growth Hacking, I think you should read some success story of Multinational brands, who grow exponentially with the help of Growth hacking techniques.
The companies known to all of us were once small startups without users and revenue. Now they have multimillion-dollar revenues and a vast customer base. That’s because they hacked growth so that you can go crazy.
Airbnb had neither users nor a reputation for a reliable service for finding and renting housing. They needed to quickly build a customer base and establish themselves in the market.
To do this, they provided users with the opportunity, in addition to publishing on Airbnb, to quickly and easily post their housing on Craigslist. This electronic classifieds site was trendy at the time. So they got access to a massive database of the target audience.
Dropbox put forward a hypothesis about the referral program: if the user and his friend, whom he invited to the service, give 500 MB each, you can quickly increase the number of new users. It was possible to share the link in two clicks and this accelerated growth.
Thanks to this referral, the number of registrations increased by 60%. The hypothesis has been confirmed, and now we all know what Dropbox is.
Facebook now has over 2 billion users. They managed to achieve such numbers with the help of their hack machine.
One of the hypotheses was an email newsletter with a notification. The user was mentioned in the post or posted a photo with him. This helped to increase the number of returns to accounts.
So what does it take to repeat the same success? We will tell further.
Why Growth Hacking
Growth hacking helps companies achieve multiple growths by constantly testing hypotheses. Multiple growth is the growth of a company two, three, five, ten times and so on.
How fast you grow up directly depends on the number of hypotheses and experiments being tested. The more tests, the more likely it is to multiply growth.
What does it mean to test hypotheses
Just like physics, Einstein first formulated the hypothesis, and then he experimented for a long time to confirm it.
As a result, Einstein found that the results of the experiments contradict the generally accepted theory, but this only prompted him to build a new theory based on the data obtained. And he did not fail.
A hypothesis is an assumption that requires proof. In the case of grows hacking, this assumption is aimed at rapid growth. And the experiment is conducted to confirm or refute the hypothesis. That is, a hypothesis is an assumption, and an experiment is the very process of confirmation or refutation.
Suppose that if we install online chat on our site to communicate with customers, we will increase sales by ‘X’, this is a hypothesis. Next, we will conduct an experiment: we establish a chat, and we monitor calls and sales.
Sales grew, thanks to chat, which means the hypothesis was confirmed.
A hypothesis is a risky assumption that a metric will behave in a certain way if we change something. Most often, this is a statistical experiment.
The whole point of the growth hacking process is to put a lot of hypotheses and quickly test them using experiments.
Why test a lot of hypotheses
Let’s say you want to grow fast and start testing hypotheses. In a week, you can verify one hypothesis. There are 52 weeks in a year, subtracting holidays and holidays – 44, minus a couple of weeks for sick leave, meetings, conferences, etc. comes out. So, we have 42 working weeks in a year.
If we test on a hypothesis per week, then we will check 42 in a year. It seems to be not bad, but experience suggests that out of ten hypotheses, only one is successful. And this means that out of 42 hypotheses in a year, only four will burn out. Imagine that each of these hypotheses brought you 3% growth. In total, it turned out 12% per year. Not very similar to explosive growth.
And if you start testing 300 hypotheses per year? These are about 30 successful hypotheses with an average growth of 3%, and a total of 90% of annual growth. Already a little impressive!
But not everything is so simple, and in order to test five, ten or one hundred hypotheses per week, you need a well-established testing process:
- A hypothesis production plant,
- Continuous experimentation, and
How to start the hypothesis pipeline
You will need a growth hacking team that will devote all their time to generating, prioritizing, testing and analyzing hypotheses. As we already know, the more testing is carried out, the higher the chances of getting explosive growth.
Who is the Growth Hacker?
As a Growth Hacker is such a hybrid of a marketer and a programmer.
Answer for the question: “How to bring users to the product?” could be “With the help of A/B testing of landing pages, hacks with virality and delivery of mailings.”
Growth hacker always relies on data and quantitative measurements and draws conclusions only on their basis. It is such growth-oriented people that will be needed in the growth team.
The selection of the team itself should begin with the growth of the master – the person who will be responsible for team processes, plan sprints, and also manage the testing process.
It isn’t easy to clearly define positions in the growth team. And full-stack specialists are valued, because there are many tasks, and hiring specialists separately for each is too expensive. You must have people who can perform functions in area of:
· A marketer who knows everything about channels and traffic,
· designer, preferably a UX developer.
“Growth hacking is doing something very quickly from shit and sticks. A designer can only slow down the work, so there should be someone in the team who knows how to make landing pages, buttons, and so on quickly.”
The main goal of the Growth Hacking team is growth. The main task is to test the qualitative hypotheses quickly.
Now that you have a growth team, it remains to build the process itself of generating ideas for hypotheses, testing them and further analyzing them.
Growth Hacking: How To Build A Continuous Growth Hacking Process
Now dive into the more practical part of Growth Hacking.
How to make everything work, so the growth team can continuously generate, prioritize, test and give successful hypotheses to production?
Just in this, we will be helped by the pyramid of Sean Ellis.
Sean Ellis is the same person who coined the term Growth Hacking in 2010. He tried to assemble a team of people who will search for growth points in the company, and marketers did not fit this requirement and did not understand what was required of them.
Key Growth Success Factors
So, what does it take to grow multiple times? Sean Ellis explained the growth criteria for growth hacking pyramid.
The basis of successful growth hacking is to form a market fit product, in other words, the specific value of the product for users. If the product is not exciting to anyone, no hacks with the offer to give the product for free, for life and even after death, will not help to grow multiple times.
Separately, it is worth noting that in the pyramid, all parts are interconnected. Without PMF(Product Market Fit), the second and third stages cannot be carried out and vice versa.
The next step in the pyramid is research that will create favourable conditions for scaling growth. At this stage, it is crucial to understand who our users are, why they use our product.
What kind of research is this?
From the funnel AARRR and Lean Canvas to the construction of CJM and Job Stories. Research helps to get to know users better, and also shows bottlenecks and provides new ideas for hypotheses.
Now that we have PMF in our hands and we know everything about our customers, we can move on to scaling growth. And we will crack growth using the construction of hypothesis testing processes.
Growth Opportunity Research Tools
Tools allow Growth Hacking teams to work more efficiently and generate more qualitative hypotheses. Growth Hackers did not invent all these tools. They are used, not only for testing hypotheses but in general for better work of the company.
AARRR funnel allows you to make the testing process holistic. It often happens that marketing is only involved, and the product is in all other stages. Hypothesis testing is random and therefore, ineffective.
Building a funnel will help break down user interactions into phases and conduct experiments throughout the funnel.
“At the stage of attraction, hypotheses about channels of attraction are tested. One of the goals is to increase conversion by lead generation. At the activation stage, experiments are conducted about the user experience inside the product. At this stage, it is important to determine the client’s aha moment. And so on down the funnel. Test hypotheses at each stage of the funnel. If you do not have traffic during the hold phase, test the hypothesis above in activation.”
This tool helps you look at the product from a strategic point of view, and the team helps you find growth points outside the product.
Customer Journey Map
Building a map will help identify bottlenecks in the product and test hypotheses in these areas.
The theory of “Work” allows you to put better hypotheses with an emphasis on the true value of the product for users.
This is not a complete list of mechanics for research, but rather the minimum set for high-quality work on testing hypotheses. And remember:
How to build a continuous hypothesis testing process
There are four stages in the growth of hacking: generating hypotheses, prioritizing backlogs, testing, collecting the data and analyzing it. Then the cycle repeats again and so on until you hack the growth. Boom!
So, you have a dream team of Growth hackers, or for starters, there is only one, but very cool growth hacker. It’s time to rush into battle and start generating ideas for hypotheses.
The main ideas for hypotheses are taken from research – the more you research, the more quality experiments.
Hypothesis generation checklist:
- We create a backlog with ideas on hypotheses;
- Note at which stage of the AARRR funnel the hypothesis is tested;
- Indicate the expected result from the hypothesis;
- Note metrics that will be affected by the hypothesis;
- The hypothesis should be formulated in the format: If _____, then _____.
Tip: try to attract the whole company to the generation of ideas, so you will surely collect a massive backlog of hypotheses. And among them, there will be those about which the growth team itself could not have guessed.
Someone in the support team knows everything about the difficulties that customers face, someone in sales knows everything about what customers want from the product at the beginning of the funnel.
This is how the growth hacking team board should looks like (This is only an ideal representation):
All ideas or hypotheses, growth team writes to any project management tools with tags, depending on which stage of the funnel these hypotheses will affect. After the rally, hypotheses are selected for implementation, and a sprint is planned.
Let’s imagine that we are working in the growth team of a company that is engaged in environmental innovation.
One of our products is a rental service for everything in the world: cars, furniture, light bulbs, appliances and so on. It’s like car sharing, just absolutely anything. We need to test the beginning of the funnel and generate ideas for hypotheses at the acquisition stage.
Here are some ideas for hypotheses. This is our list:
- If you make the registration button in the service larger, the CTR will increase 1.6 times;
- If you run creatives on social networks, the number of registrations will increase by 30%;
- If you offer the user a free subscription for three months to an HD-TV and a robot vacuum cleaner, after the subscription expires, he will renew it for a year.
- If you write on the landing: “Rent, save on purchases, spend on impressions and save nature,” the conversion to registration will increase 1.7 times.
- If you place photographs of houses and apartments with the latest technology for rent on the landing, the conversion to registration will increase by 2 times.
Now we have to hook up all the ideas at the grow-up meeting and prioritize them.
After generating hypotheses and sending them to the backlog, the time has come to analyze and prioritize.
The entire growth team should be involved in prioritizing hypotheses, not just one person. This will help to objectively select better hypotheses into work and remove non-urgent or too dubious hypotheses.
For proper prioritization, it is necessary to calculate how quickly the hypothesis can be launched and how long it takes to test it. As well as what effect it will have on growth.
The hypothesis assessment method ICE Score (Impact, Confidence, Ease) can help in prioritizing hypotheses. Using this technique, you can determine the degree of influence on the necessary metric, ease of implementation, as well as confidence in the hypothesis.
After all the hypotheses have been prioritized, we select those that we will test in the next sprint.
We will return to our eco-service for renting various amenities.
When prioritizing hypotheses, remember what results from the hypothesis you want to get, which metric it should affect, and that the implementation should take no more than six hours.
After we prioritize the hypotheses by ICE, we select those, that scored the most points and take them in the sprint and leave the rest in the backlog to wait for the next time.
We got to the top photos on the landing page, copywriting on the landing page and a free subscription, we will implement them. Remember that the more quality hypotheses you test, the higher your chances of success.
At this stage, we launch hypotheses: create landings, conduct A / B testing, redo the offers on the site, change the path of the user session, and so on.
It is essential that the time to launch the hypothesis be limited, this will allow you not to test more.
But after the launch, the data can be collected as much as desired: one day, week, month.
At the stage of experiments, we implement our three hypotheses: we update headings and photos on the landing page and make a free subscription. What’s next?
Information Collection and Analysis
After conducting experiments and testing, it is necessary to record the conclusions of the hypotheses in one document. The better the document with experiments is arranged, the easier it is to analyze and understand where to go next.
A well-structured document will also be needed in the future in order not to start testing the same hypotheses accidentally.
Now we know that a free subscription to the service gives good results, and changes in the landing have so far failed. We conclude that a free subscription needs to be worked out qualitatively already in the product, and landings should be tested for other hypotheses.
So let’s summarize: