Building an API for powerful customer data analysis

Inside Intercom

Today we’re delighted to launch our brand new API version 2.0 , which makes it easier for our customers to pull, analyze, and update Intercom contact and conversation data. It consists of an overhauled Conversations API, as well as brand new Contacts and Data Attributes APIs.

Data Lake Engines - The Essential Layer of the Next Generation Data Architecture

Tom Tunguz

We shared a vision for a new way of working with data. More data is being stored in data lakes like Amazon S3 and Azure Data Lake Storage. There needs to be a layer between them to make all that data accessible to these users - a data lake engine.

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Series A SaaS Startup Benchmarks for 2018

Tom Tunguz

But the average MRR has increased substantially from the last time I analyzed the data. The usual caveats to this data analysis apply. How far along was the typical SaaS Series A in 2018? The median business was at $1.8M in ARR and growing at 250%.

Data, Data Everywhere, Not a Second to Think

Tom Tunguz

More and more companies realize their proprietary data contains insights that drive tremendous competitive advantage. Enabling an organization to make data driven decisions is a long term process. Companies build or buying the tools and expertise to store and process that data.

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Say Goodbye to Excel Forecasting


If you expect them to input data into a spreadsheet, you will get the bare minimum in return. As a result, you are unlikely to have the data you need to identify the opportunities and risks necessary to accurately adjust your forecast. Lacking invaluable data.

Why “Closed Reason” is the Secret Weapon for High Performing Sales Teams


“Closed Reason” is one of the most valuable, yet underutilized, pieces of data that a sales organization can collect about its opportunities. To help you take advantage of this trove of intelligence, we’ve compiled some interesting results based on how our customers employ Closed Reason data.

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Dashboards & Automation Drive Team Efficiency – A Success Story


While the team had the ability to view aggregate customer data, it existed in a web of unorganized spreadsheets. Uncovering customer insights required time-intensive manual analysis. Dashboards & Automation Drive Customer Success Team Efficiency – A Success Story . .

Reaching Rockstar Admin Status


Our data refreshes took a long time and we needed answers quickly. Plus, there was a lack of consistency across teams in terms of the reporting format and selection of data and metrics for measurement. “Slowness to change usually means fear of the new.” – Philip Crosby.

Sales Brief: guaranteed sales, freemium vs trial, analytics, and more

This week we cover some great reads on the topic of sales data. Gong published a set of sales tips based on data collected from real sales conversations. Some of the data they present is super surprising. WHO'S YOUR DATA? ?. TIME TO HEAD DATA WAY ?.

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IVR Payments for Insurance Premiums

Agile Payments

Automating payments meant that the Insurance company had to have a PCI compliant solution that did not expose sensitive card data. Data analysis and tracking allowed the Insurance company to measure automation rates and to monitor how customers used the IVR payment application.

Winning with Data

Tom Tunguz

There’s a new class of company that wield data to create long-term competitive advantage. TheRealReal uses this morning’s sales data to inform this afternoon’s marketing campaigns. I first saw the impact of this type of data informed decision-making at Google.

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2020 SaaS C-Suite Evolving to Support Product and Customer Lifecycle Management


Metrics and analysis of customer and the product lifecycles is fundamental to growth decision-making in a SaaS company. This structure integrates systems and data, ideally resulting in tight management of the quote to cash process.

What to look for when hiring a data scientist

Tom Tunguz

But a more important driver has been the need to better understand how to qualify, evaluate and hire data scientists because data science is a massive competitive advantage. And many of the companies I work with are hiring data scientists. Data processing. Data analysis.

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The Future of Human Data Interaction

Tom Tunguz

On the day of Tableau’s IPO, a company known for innovating in data visualization, I thought I would share the most impressive HCI concept I’ve seen in a long time.

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How to perform a sales analysis (step-by-step with methods & metrics)

You need cold hard data, and your sales CRM must capture all necessary information on the deals closed by your reps. To improve your sales effectiveness and make informed data-backed decisions, you need to conduct sales analysis regularly. Top 10 sales analysis metrics and KPIs.

A Missive to Marketing: Impose Simplicity


Precise titles and hierarchical levels aside, there are two different animals: data analysts and data architects. And a VP of data architecture thinks a lot more like a director of data architecture than a VP of data analysis. Markets are complex.

Startup Best Practices 21 - Your Startup's Recruiting Scorecard

Tom Tunguz

For example, a data engineering role may require familiarity with data analysis tools. The same data analysis job would require an ability to learn new technologies and simplify complex data into comprehensible insights for the rest of a team. Last night, SaaS Office Hours at Redpoint welcomed Maia Josebachvilli , the VP of People and Strategy of Greenhouse. Maia is a thought leader in human resources.

How to Run a Regression Analysis to Forecast the Return on PPC Spending

SaaS Growth Strategy

Regression analysis was a tool that could help me. Based on your historical data, you can then forecast what the return will be at higher spending levels assuming that there’s a linear relationship between the two variables. Download Excel’s Data Analysis Toolpack.

The 8 Biggest SaaS Trends of 2020


In 2020, your data has never been safer or easier to use, emerging trends have never been more exciting, and we’ve never been more connected to the people around us. 90% of mobile data traffic will be generated by cloud solutions/SaaS by 2019.

Best Way To Successfully Launch A Digital Marketing Campaign Through Social Media


Developing the ability to utilize social data will put your brand at the forefront with all the other successful brands you can think of. This will make social data easier to analyze, too, as you will be looking for patterns and trends that are in line with your company’s vision.

Customer Success vs. Customer Service: How They Work Together


It involves taking customer data insights and turning them into strategic actions that will help your customers achieve their business goals (which, in turn, will help you achieve your own). A successful organization operates in much the same way as a prestigious orchestra.

How to Combat Inaccurate Data and Faulty Statistics When Making Decisions

Tom Tunguz

The conclusions were results of bad experimental design, biases in the data , and statistical tools used incorrectly. One of the major problems with data analysis are the imperfect methods we use. But p-values doesn’t answer the question to the answer most people care about: what are the odds the hypothesis about the data is correct? In addition to dissolving faith in the research process, bad data encourages wrong decision-making.

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The Technology that's Taking Data Science by Storm

Tom Tunguz

Amazon’s Redshift, an elastic data-warehousing solution launched in late 2012 is the most salient example. Redshift’s ability to process huge volumes of data is breathtaking. When running Redshift on solid state drives (SSDs), one team at FlyData queried 1 terabyte of data in less than 10 seconds. AirBnB’s data science team wrote about their experiences contrasting Redshift and Hive.

The only sales enablement job description template you need to attract killer candidates

Strong analytical skills and ability to interpret insights from data. Nice-to-haves: And these are the ideal-but-not-required skills that would help them do even more within the role—think coding knowledge, data analysis experience and familiarity with your industry.

Cohort Analysis for Startups: Six Summary Reports to Understand Your Customer Base (With Code)

Tom Tunguz

Cohort analysis provides deep insight into customer bases because cohorts expose how customer accounts grow, evolve and churn. Plus, cohort analysis provides a framework to evaluate product releases, marketing pushes and advertising campaign performance.

Startup Trends from YCombinator's Demo Day

Tom Tunguz

This increase in activity seems to be driven by advances in data analysis for drug discovery and novel sensors. If this data is any indication, we should see more commerce and consumer finance companies; and more vertical software businesses in the next few years I’ve been to many YC Demo Days and I always look forward to them. This year was no exception. There are so many wonderful ideas and companies founded by terrific entrepreneurs.

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Hiring the Right CMO for your Company

OpenView Labs

The most important hard skills to look for as you vet applicants include: Management, expertise, data analysis and financial understanding.

B2C 75

What does effective experimentation entail?


Bad experiments are used to defer decision making, settle disagreements, or let the data tell us what the right thing to build is. They have strong, well-reasoned hypotheses grounded in data analysis, customer insights, and market research.

Why Personas Are Critical Product Development and Go To Market Tools for Startups

Tom Tunguz

When the data analytics team took the stage, I listened with great interest as the chief of the group described their internal struggles with data and the areas where startups might help them achieve their goals. I’ve summarized these personas below: The Three People That Matter in Data. Analyst Reveal trends in data Create and propagate data silos Visualization tools, Spreadsheets, BI. For example, I’d never heard the term data steward before.

Against All Odds in Startupland

Tom Tunguz

Win probability charts like the one above have become the icons of popular predictive data analysis. I love data, but let me whisper a heresy to you. The problem with predictive analysis like this is they never capture all the variables. Predicting the future is damn hard, and no matter how much data we jam onto disk, or how sophisticated our adversarial neural networks become, we still won’t be able predict the future accurately.

An Exceptional Story with Exceptional Data

Tom Tunguz

Even if you’re not a soccer/football fan, the article is worth reading because it’s one of the finest examples of synthesizing data and a story to convey a point I’ve read in a very long time. Data is one of the most powerful ingredients to supporting a point of view. It’s one of the reasons I publish data analysis on this blog. But data alone isn’t enough - not nearly enough - to be compelling.

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The Benefits of a Data-Driven Sales Enablement Strategy

OpenView Labs

The Power of Positive Correlation Analysis. For example, by comparing your skill gap analysis with internal, Customer Relationship Management (CRM) data, you can pinpoint the skills that show the highest correlation to quota attainment (or other vital KPIs ).

Your Startup's Competitive Advantage

Tom Tunguz

A better chat experience ; a data modeling layer for data analysis, near-instant transcription of expenses. Startups fail when they run out of money. Startups run out of money when they lack focus. Without a maniacal focus on serving customer needs in a unique way, startups can flounder amidst competition. Without product market fit, the business is challenged to generate strong metrics and faces fundraising challenges.

“What’s a good conversion rate for my landing page?” [New AI-Backed Research]


Our benchmarks reveal data-supported best practices, and you’ll waste less time and traffic testing unproven optimizations that our machine learning analysis shows don’t necessarily work. Our data, however, complicates this equation.

Pricing analysts 101: What does a pricing analyst do? [+ qualifications]


Our pricing analysts build surveys and use ProfitWell’s algorithm to collect actionable data to guide business strategy in a manner that is measurable and implementable. To keep up with the ever changing market behavior, analysts also conduct research on subscription market analysis.

The best way to organize your marketing stack


In this stage, it’s critical that you use tools and integrations that help you collect user data and put insights into action. You went to your CRM app to track leads, set up social campaigns on your scheduler, and created emails without user data. Data Integrations.

The Top 5 Customer Escalation Best Practices You Need to Know


Part of molding your business to your customer’s needs involves making customer data accessible to all team members. Gathering and sharing customer data across the company helps you take a more proactive approach. A quality customer success platform gives you access to the customer data you need to turn escalations into success. Signalization: Use this data to accurately determine a customer’s current situation and future needs.

The 12 Things I Know About You

Tom Tunguz

But as I’ve learned writing this blog, experimentation and data analysis will lead authors to share those insights in the most generalizable way possible. I know 12 things about you. You have a great need for other people to like and admire you. You have a tendency to be critical of yourself. You have a great deal of unused capacity which you have not turned to your advantage. While you have some personality weaknesses, you are generally able to compensate for them.

Gorgias Improves Account Insight and ROI Attribution with Hull


Improve ROI attribution and intelligently measure channel performance by cleaning up marketing lead source data. Prioritize visibility and transparency throughout the company with data-driven dashboards and account-level insight. Data plays a significant role in the culture at Gorgias.

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Feature/Product Fit

Casey Accidental

Most good product development starts with a combination of data analysis and user research. For example, when we launched the Grubhub mobile app, we saw in the data when people used the current location feature, their conversation rate was lower than people who typed in their address.