Seven Steps for Growth Hacking Your Business with Data
No data? No problem. You can growth hack your way to success in seven steps.
Whether you’re pre-launch or ready to scale, data can hold the key to your business’ growth. Even if you don’t have much data about your customers or product yet, you can still use data to growth hack your business by following these seven steps.
1. Define your business objectives
Before you can shoot for the stars you need to be clear about what you’re trying to achieve. While this is often easier than it sounds, it’s a crucial step because your goal will drive your strategy.
According to Simon Mathonnet, Chief of Digital Strategy for Splashbox, it’s important to translate your objective into something practical. For example, rather than saying your goal is to grow your business, it should be more specific — like you want to quit your job so you can focus full-time on the company, or you want to raise a Series A investment round.
2. Make your objectives measurable
Once you’ve defined your objective, it then needs to be translated into something that you can track. A good way to do this is to make it SMART. This stands for:
- Specific: Make the objective clear and easy to grasp.
- Measurable: Set a quantitative goal that can be measured.
- Achievable: Get buy-in from your team and give them (and yourself) an incentive by having an objective that’s within reach.
- Relevant: Your goal needs to make sense and be in line with what the business is trying to achieve.
- Time: Be clear about when the objective needs to be achieved. This will give you something to look forward to.
The SMART objective for the two objectives above may be:
- Quit your job to focus on your startup = Generate $X of revenue per month for three consecutive months.
- Series A capital raising = Retain Y active users for three months before approaching investors.
3. Create a hypothesis
Once you’ve defined your goal you need to find a way to get closer to achieving it. One way to do this is to create a hypothesis that you can implement and test quickly. The hypothesis is essentially an educated guess or hunch based on what you know about your product or service and customers.
For example, if your objective is to grow revenue, then your hypothesis might be that people who look at three or more products on your website are more likely to purchase. This means you need to find a way to get people who visit your site to look at three or more products because you believe this will increase your revenue.
4. Collect data
To be able to test and measure your hypothesis you need to have data. The data sets a baseline — so you know your starting point — and measures your results. The type of data that you need will depend on your hypothesis.
If you’re pre-launch, you probably don’t have much customer data yet. Most startups also struggle with data because of their uniqueness — traditional, quantifiable data sources like market research may not have insights for your product or market segment. While it can be expensive to commission market research, thankfully there’s a plethora of technology that’s relatively inexpensive that can help you mine information and generate new data.
Some ways you can collect data include:
- Google Analytics: This is useful if you have had many visitors to your site. It collects data on what interactions people have on your website, like how long they spent on your site, what pages are the most popular, what search terms they used and what links they clicked.
- PoweredLocal: If you have a brick and mortar shopfront, this platform lets you collect information about your customers by offering them complimentary Wi-Fi access. When customers use social media or email to sign onto your network, you can find out who they are, what they like, and potentially sign them up to your newsletter or offers.
- Online reviews: Review sites like Yelp or TripAdvisor serve two purposes. They let people who are looking for your product or service hear what you’re like directly from your customers, and they provide a way for customers to give you feedback. This feedback is data that you can use to identify opportunities to improve your customer experience.
- HotJar: This heatmap tool lets you see how people use and respond to messages on your site by showing what they engage with. Unlike Google Analytics, you don’t need too many visitors to your site to start seeing what is attracting or repelling your customers.
- Social Media: Research social media channels to see what customers are talking about. This may be either on your own social media pages or your competitors’. Social media platforms like Facebook and Twitter also have analytics tools that are often available for free. These can show you demographic and engagement information about your audience.
- LeadChat: Use a live chat function on your website to get direct input from your customers. Find out your customer demographic and see what questions they ask to determine what they’re interested in or are struggling with.
- Events and pitch nights: Collect anecdotal data by talking to potential customers, peers and competitors. You can find them at industry events, pitch nights and conferences.
5. Design a test
Once you have baseline data, you can design a test for your hypothesis. One of the most common ways to test your hypothesis is to do a split test. For example, you could have two separate landing pages and test which one gets the best results. Optimizely is a tool that can help you design split tests on your websites.
Another way to test your hypothesis is to make a small change and see if it improves your results or not. For example, see if visitors look at more products when your website includes a widget that shows them two products that other visitors purchased.
If your testing includes advertising online, Gary Tramer, Head of Growth at PoweredLocal, suggests looking at what your competitors are doing. SEM Rush is a tool that shows you what keywords your competitors are targeting or using in ads. You could choose some of these to test out. After all, if it works for your competitors, it’s also likely to work for you.
Once you’ve designed your test, it’s time to put it into practice. When testing your hypothesis, set a timeline and monitor the test closely.
6. Analyze the data
Once you have some data from your test, you can analyze it. Has the test got you closer to achieving your objective? If it has, then look at what’s worked and see if there are any clues in the data about how you can improve the test.
If the test hasn’t had an impact, or worse has negatively affected your results, then analyze what the data is telling you. Look at how customers have reacted and listen to what they’re saying. You can then use this information to iterate.
7. Make decisions or iterate based on the results
It’s unlikely that you’ll get your hypothesis spot on the first time. To make sure you get closer to your goal, you may need to tweak your hypothesis or test and then iterate. This may involve making small changes to see what makes a difference, or making much larger changes based on the feedback or insights you glean from the data.
With each iteration, you’ll get closer to optimizing your test and finding opportunities that will help you achieve your objective. When you do reach your goal, you’re then ready to set a new objective and start the process all over again.
Watch Simon Mathonnet, Chief of Digital Strategy for Splashbox, explaining how to growth hack your business with data at the WeTeachMe Masters Series.