Today we’re sharing the full vision of TigerEye - a conversational AI analyst for go-to-market. This is a new approach to business intelligence built to adapt itself to the needs of the user.
Over the last decade, the data generated by sales, marketing and other go-to-market teams has exploded. More steps of the funnel are being tracked — from lead tracking to lead enrichment, call recording and product usage. We should be living in a golden age of analytical decision-making. Why doesn’t it feel that way?
For many of us, the volume of data is plentiful, but meaningful insights remain elusive. We’ve been let down by the tools that were supposed to bridge the data warehouse to the end user. Dashboards are slow and inefficient. Custom reporting requires us to learn complicated tools or rely on understaffed ops teams to build the reports we need. And by the time the ticket has been filed, triaged, developed and delivered, you’ve moved on to something else. When you don’t have time to wait for analysis before making a decision, you make the best call you can with what you’ve got, but the best call isn’t necessarily the right one.
TigerEye’s mission is to help go-to-market teams grow faster by making better decisions faster. Delivering this requires more than building a better dashboard. We are making it quick and easy for everybody in GTM to access and work with data. No learning curve, no internal dependencies, just questions and answers.
Today we’re sharing the full vision of TigerEye - a conversational AI analyst for go-to-market. This is a new approach to business intelligence built to adapt itself to the needs of the user. Centered around a familiar chat interface we call TigerChat, TigerEye partners with every single person on the team to provide thoughtful insights to any question. From quick pipeline check-ins to complex analytical queries, TigerChat can answer just about anything. We take care of connecting all the data, you just bring the questions.
Let's take a look at a few examples:
A simple question about pipeline and forecast is a great place to start. TigerEye shows the current actual, target and AI forecast. All views in TigerEye are filtered to match the user’s data access level, based on rules each customer defines.
Let’s try something a bit harder. TigerChat is great at understanding complex prompts like this one: “Show me a table of close cycle by quarter. Rows include the rep's name, columns have the actual close cycle and the percentage change from the previous quarter.” Here I’ve told TigerChat exactly what I want to see.
TigerChat is always thinking in the context of GTM, and has a native understanding of core concepts like close cycle and fiscal quarter. TigerChat considers the prompt and decides how to answer. When a custom report is the right answer, TigerEye creates SQL and runs the query locally. It is easy to see the full query and a simple explanation of how it works.
We’ve been looking at core sales questions, but TigerEye knows top of funnel as well. Let’s look at lead sources.
TigerEye quickly summarizes the effectiveness of different channels and can track performance changes over time, campaign, region and more. This response defaulted to ‘all time’ because we didn’t specify a time period. TigerChat is conversational, so if we add more specifics like “show me just this year” we get a filtered set. All views can be expanded, saved and shared for future reference.
These questions are just the tip of the iceberg. TigerEye connects to CRM, ERP, marketing automation and more to create a unified view of GTM with live sync and daily snapshots.
In addition to the new AI analyst, we’re debuting numerous additional improvements to TigerEye Today.
We’ve rebuilt the navigation for fast mobile access. TigerChat, saved views and all pipeline analytics are available instantly. No need to reach for the laptop to answer complex questions when you’re away from the desk.
Monitor pipeline health and track historical trends. This is the perfect companion for pipeline review meetings and developing an integrated GTM execution plan.
Pipeline Coverage brings the whole funnel into a single unified view. At the top of the chart we see total open pipeline by day and total closed/won actual. At the bottom of this table is a day by day change summary - how much new pipeline was added (from what source) and how much was removed. At the bottom of the page is the Pipeline coverage chart. This tracks the ratio of open pipeline to remaining target.
Pipeline Coverage gives you a live picture of how top of funnel is influencing attainment and how much risk remains for hitting goal. You can move back to a previous quarter to see how the current period differs and you can filter by segment, lead source and more.
Radar tracks key changes in the business and creates an AI summary to catch you up on what has changed since your last login. The default prompt generates a broad overview, but can be customized to prioritize what’s most important to you.
TigerEye writes high quality SQL, but there will always be reasons to make changes (or roll your own). Data Explorer is a feature-rich query builder designed to help analysts write powerful queries fast. From full-schema autocomplete to stored snippets and IDE-like developer power tools, Data Explorer delivers.
User roles determine what features and data each person has access to in TigerEye. Simple data scoping rules allow you to define who can see everything or just data for their own team. Create as many roles as you need.
Change chart elements, styles and more with our simple chart builder.
We’re thrilled to share TigerChat and the full AI Analyst vision with the world. To see it for yourself, schedule a demo today.
Stuart Frederich Smith, CMO of TigerEye has built a history of leading great teams and launching impactful campaigns. With more than two decades of experience in marketing, product and operations, Stuart is a cross-disciplinary leader committed to collaborative execution. He holds a BA in Film, Television & Theatre from the University of Notre Dame and lives with his family in Portland, OR.
