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Despite many pretenders to the Google Analytics throne, the service continues to dominate web and marketing analytics for small and enterprise-grade businesses alike. But popularity and omnipresence aside, there is always room for improvement.

Over the years, many Google Analytics users have requested that Google produce an annotations API to enable web and marketing professionals to automate the process of adding contextual notes to Google Analytics, helping them figure out what events on a specific day spiked or decimated traffic. One of those users was Fernando Ideses, founder and CEO of a fledgling Israeli startup called GAannotations, which is emerging from stealth today with $1.2 million in funding to develop a tool he had wanted Google to offer natively. “After having no success with the requests, my team and I decided to take a stand,” Ideses said.

While Google Analytics is fine for serving information on how end users engage with a website, what pages they spend the most time on, and so on, the data often lacks sufficient context. “How do you remember all the changes and improvements you made that affected your website, and what works?” Ideses said. “This question is why we created GAannotations — to add annotations in bulk.”

Cause and effect

It’s worth noting that Google Analytics already has a native annotations feature, but it’s a manual process that offers little in the way of automation via external APIs and integrations. Users can click on a date in a timeline and enter a description into a text box that explains what they did on that date — for example, rolling out a new software update or launching a marketing campaign. This helps create a narrative of sorts, with anyone in the company able to hover over a timeline’s peaks and troughs to see what was going on behind the scenes that day.


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Above: Google Analytics’ native annotations

GAannotations builds on this by making it easier for marketing and analytics teams to create contextual notes by ingesting data in bulk from third-party sources through its API. The company has also created tutorials to help non-coders leverage Zapier to integrate with the likes of Google Ads, Mailchimp, Shopify, Slack, Asana, Trello, Jira, GitHub, and Bitbucket. This means it’s possible to correlate a Mailchimp marketing campaign or a new product that has been added to a company’s Shopify store with activity tracked by Google Analytics.

Above: GAannotations: Integrations

Additionally, GAannotations ships with a bunch of prebuilt integrations with external data sources around public holidays, retail events such as Black Friday, Google algorithm updates, Google Ads history, and even the weather.

Above: GAannotation: Data source integrations out-the-box

With the GAannotations Chrome extension installed, marketers can instantly see the impact of adding Black Friday-related keywords to a website landing page, for example, and whether a new display ad has had the desired effect, a software update has improved traffic, or that week-long snowstorm drove pageviews for a specific product.

Above: GAannotations: The impact of Black Friday-related keywords to a website landing page

GAannotations runs a freemium business model, starting at free for individual users — with restrictions on manual annotations and CSV uploads. The basic plan costs $19 per month for a single user, but it includes access to the annotations API, while $99 unlocks access for unlimited users and Google Analytics accounts, access to external data sources (e.g. holidays), and more.

Above: GAannotations: Pricing

There is at least one similar tool on the market, but GAannotations is hoping the breadth and flexibility of its data integrations will set it apart. Now, with funding from an under-the-radar Argentinian VC firm called Madero VC, the company has enough in the bank to grow its business beyond its early-stage customers and target everyone from small indie developers to big businesses and marketing teams.

Ideses said the company plans to use a significant chunk of the money to add more metrics and analytics to the mix, including simplified table comparisons when using multiple data ranges, table heat maps to help visualize and compare data, and more.

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