There’s a secret only a technologist would know. Search queries contain user behavior data. Data that is critical to know your customer. It’s so critical, I’m claiming it can help with product-market fit.
There are indicators for absolutely everything. A quick Google search can lead you into a rabbit hole of metrics, indicators, reports, and examples. I’m here to explain what indicators matter to your business and the secret about search.
If you’re a maker, entrepreneur, co-founder, angel investor, VC partner, or VC analyst, then please continue reading. You’ll know exactly how to hardwire into your customer’s brain.
There are two sides to this idea. Before and after product-market fit. We’re focusing on the before.
It’s important to note that if you haven’t achieved product-market fit, you are on a time limit.
You can extend that time limit with capital but the default scenario is death.
“I use the metaphor that a startup is like throwing yourself off a cliff and assembling an airplane on the way down.
Product-market fit is about trying to steer away from the default. To not only survive from death but to prosper out of the process of surviving. To do so, as founders, entrepreneurs, and makers, you need more than the default indicators.
I’m going to be quick here with listing what you need to know.
Each one of these indicators could be its own blog post so the brevity is intentional.
Note: If you have a great article or video to recommend that associates with any of the bullet points below, please post them in the comments. I’ll credit your LinkedIn, Twitter handle, or website. It’ll be a quality backlink in the future 😉.
When I talk about search. I’m referencing a search box. Any search box you’ve seen on a website is exactly what you need to be imaging in your head.
The search results are irrelevant throughout the post. We’re hacking the search box to dive deep into the user’s mind.
Marketers haven’t tapped into their product or website search yet, but it doesn’t mean this is an unproven technique.
Marketers have been mining user behavior queries on Google for years. It’s a proven process.
Everyone is already data mining Google but nobody is data mining their website or mobile search.
Google Trends is too macro for us to figure out product-market fit.
For you to obtain the right kind of data, you need to search on your website or mobile app. Do you have search? Is it on your blog? On your homepage? Is it in your bot?
This is where the value is.
One of the holy grails to user behavior data. It’s better than heat maps. Better than Behavior Flows on Google Analytics. It’s where you can leverage untapped potential and start to collect early data.
Here’s what you can find out
Search query data is like having a custom-tailored Google Trends. It’s hyper-focused on your product and marketing efforts.
The hardest part is understanding how it works and unpacking all the data into actions you can execute on.
Warning: This small section is a bit nerdy.
Here’s a list of data points to collect while users are typing in a search bar. If you want this taken care of for you, I suggest you try out ChipBot.
For this method to work, you can’t just slap search onto anywhere on your website. It has to be an intentional position that drives real results.
A search bar is located in the global header on your website, on your customer support page (like a knowledge base page), and in your support bot.
Placement is key because you’re trying to catch users when they want an expedited experience or ran into a problem and need help ASAP.
Before a user bounces, they’re going to be looking for one the three positions mentioned above.
Once you’ve implemented some type of app or website-wide search, it’s time to start finding trends and creating measurements.
This is key 🔑 . Trends can help you establish what metrics to focus. Once you measure, you optimize. This will be your north star for product-market fit.
The easiest way to find important subject terms in search queries is to borrow the idea of a tag cloud. But instead of a tag cloud, use a search cloud!
Search clouds help you find common trends in your product or marketing implementations. Founder and marketers can make quick deductions based on common phrases and usage.
Look for false-positives in your product search trends. Don’t assume all requests and search queries are pathways towards a great product.
When you’re observing search queries, you want to weight some terms over others. This is a manual effort the business works out and requires additional review from all the team members in the company.
For example, you may want to filter out search queries around “how to install” if users are installing the product. In the example above, I filter out “customers”. We already know it’s high on relevancy but it’s not descriptive by itself.
Trends and metrics alone won’t solve anything for you. You need a full cycle of analyzing, implementation, and retesting… for which I’m dubbing as A.I.R.
I’m an example-driven kind of person, so let’s start out with a real-world example from my company during late 2018.
First, we looked at trending queries that we captured through ChipBot. This was easy since we could observe both the formal questions and search query report.
Next, we came up with some educated guesses.
Now that we have some ideas, let’s gamble 🎲. We created tickets on GitHub Issues to start tracking our implementation efforts. Then we got to work in both product and marketing.
Note: At ChipBot, we currently have all website development owned by the product team. Your business may run the website under the marketing team.
Here’s what we implemented:
Next was to test and find new results. And the results were in line with what we were theorizing.
Results from tests:
The best part of this was we were using our own product to improve the product. It’s a really good feeling to see value come back full circle.
Instead of people confusing us with chat, they wanted a deep comparison of ChipBot vs Live Chat or ChipBot vs Chatbots. After all, we were competing for that little icon space on the bottom right.
The next surprise actually led to a serious brand and vision discussion within the company. That led to an understanding of where our value is most understood at. Validated by customer interactions and our indicators.
We can be confident in how we help businesses, with or without our product. Our vision supports this model.
Now, I’m perfectly OK recommending Intercom or Drift if a business will perform better with it than with ChipBot. I’m not here to become a decacorn company, I’m here to create you something valuable and unique.
You can quote me on this. After all, my company is building a bot to assist with this. And we’re building new models to make these behaviors identifiable with machine learning.
Search is an essential indicator to know if your customers care about you and your product. Combined with early and lagging indicators, you’re going to have an advantage with other startups.
By knowing your data points, you can confidently grow your business or you can pull the plug early before losing a bunch of money and time. For us, there’s always a new opportunity to find, so let’s do it in a data-driven way. Let’s hack technology to show where value can be discovered.
Matt is a Chicago-based entrepreneur and hard-working founder of his startup ChipBot. Knowledgable in 12 different programming languages and experienced startup veteran; having worked on 6 others. He focuses on solving hard problems using clever engineering and wit. You can reach Matt on Twitter, LinkedIn, or StackOverflow.