Top Tech Companies Ranked By Engineering Retention

(TL;DR) Here’s the ranking going from top to bottom (so higher / longer the better):

eng_ret

How did you measure this?

By running advanced Linkedin searches and counting up the hits. Specifically, for each company, at their headquarters location only, I searched for profiles that were or are software engineers, and had at least 1+ years of experience. Then I filtered these results in two ways:

1) Counting how many of those profiles used to work at the company in question (and not currently). Call this result Past Not Current Count.

2) Separately (not applying the above filter), filtering to those who are currently working at the company for at least 1+ years. Call this Current Count.

I also computed the number of days since incorporation for each respective company to be able to compute Churn Per Day – which is simply dividing Past Not Current Count by the number of days since incorporation.

Then I took this rate, and computed how long in years it would take for each company to churn through all of their Current Count or current heads who were or are software engineers and who’ve been with the company for at least 1 year (those who possess the most tribal wisdom and arguably deserve more retention benefits). Call this the Wipeout Period (in years) figure. This is what’s plotted in the chart above and is represented by the size of the bars – so longer the better for a company.

What does the color hue indicate?

The Churn Per Day (described in the previous answer). The darker the color the higher the churn rate.

Who’s safe and who’s at risk?

I would think under a 10 year wipeout period (esp. if you’re a larger and mature company) would be very scary.

In general (disclaimer – subjective – would like to run this over more comps) greater than 20 years feels safe, but if you’re dark green (and hence experience more churn per day) then in order to keep your wipeout period long you need to be hiring many new engineering heads constantly (but you may not always be hot in tech to be able to maintain such a hiring pace!).

What are the caveats with this analysis?

There are several, but to mention a few:

Past Not Current Count biases against older companies – for ex. Microsoft has had more churn than # of present heads because they’ve been in business for a long time.

I needed more precise filtering options than what was available from Linkedin to be able to properly remove software internships (although could argue that’s still valid churn – means that the company wasn’t able to pipeline them into another internship or full-time position) as well as ensure that the Past Not Current Count factored only software engineers at the time that they were working at that company. So, given the lack of these filters, a better description for the above chart would be Ranking Retention of Folks with Software Experience.

Also, this analysis assumes the Churn Per Day figure is the same for all folks currently 1+ years at their respective company, even though it’s likely that the churn rate is different depending the # of years you’re at the company (I’m essentially assuming it’s a wash – that the distributions of the historical Past Not Current vs Current are similar).

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Want to compete with Salesforce? Buy Marketo

An op-ed I wrote for TechCrunch:

There are several enterprise players that want a share of Salesforce’s business, but just aren’t making headway by knuckling up against the company’s dominant, entrenched SaaS CRM offerings. Rather than competing head on, a smarter approach for these businesses is to “front door” Salesforce, instead.

By acquiring Marketo, a competitor could get into Salesforce’s accounts, then, over time, work themselves down the funnel and leverage better integrations with Marketo in order to eventually displace Salesforce. Marketo’s strategic foothold in the enterprise and its current market value relative to potential acquirers like IBM, Microsoft, Oracle, SAP and even Salesforce make this a great time to buy the leading marketing automation vendor.

Many industry watchers overlook the mission-critical role Marketo plays in its customers’ go-to-market operations. The majority of Marketo’s 4,000 customers also use Salesforce, but the marketing automation system has access to more data about the funnel than its CRM counterpart. Marketo can sync bi-directionally with Salesforce, capturing all the data stored there, while also holding top-of-the-funnel lead behavior data that doesn’t get stored in CRM. Hence, it has access to an invaluable superset of data about a company’s potential and existing customers.

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How sales is disrupting marketing

An op-ed I wrote for VentureBeat:

The line between marketing and sales is getting blurrier by the minute. Sales reps are leveraging new sales acceleration tools like Tout, Yesware, Sidekick, and Outreach, and it feels like a new one comes out every quarter.

These specialized apps have become so sophisticated that they’re enabling sales to run their own campaigns and sidestep marketing automation. They help teams increase response rates through more personalization and control, a 1:1 touch, simple plain text messages, and more follow up vs. blanket general marketing blasts.

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Calculating LTV and CAC for a SaaS Company on a Rolling Basis

An op-ed I wrote with Tomasz Tunguz for Techcrunch:

One of the most critical metrics for software companies — but also one of the most difficult to measure — is the lifetime value of their customers (LTV). The lifetime value dictates how a company should spend its marketing and sales dollars.

Unfortunately, many early stage startups struggle to measure LTV, because they haven’t been around very long and, consequently, haven’t seen a large number of customers through their lifespans with the product.

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The Future of Marketing Automation

An op-ed I wrote for TechCrunch:

According to industry expert David Raab, almost 70 percent of marketers are either unhappy or only marginally happy with their marketing automation software. According to Bluewolf’s new “State of Salesforce” study, only 7 percent are seeing good, measurable ROI from those investments. There’s a lot of fragmentation and dissatisfaction in this category despite the huge potential benefits of automating marketing.

A key contributor to the current state of marketing automation is the fact that its roots stem from email blasting. As these systems layered in landing pages and forms, web activity data, triggers, etc. over time, they became bloated from trying to do too much and began to over-promise and under-deliver.

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How LinkedIn Could Take On Salesforce

An op-ed I wrote for TechCrunch:

Today’s B2B sales and marketing folks struggle with the overwhelming number of channels for finding and reaching new leads. The customer “funnel” continues to expand as buyers do more of their own research before raising their hand to connect with a sales rep. But imagine if you could make the funnel taller by identifying leads when they’re just browsing your site and haven’t yet filled out your “contact me” form, or leads who haven’t yet visited but are likely to be a good fit for your product? That’s hard to do with the primitive tools that are available for sales and marketers today, unless you bring together some very rare assets – which just so happen to all exist at LinkedIn.

LinkedIn is the only company with fairly clean, accurate details on pretty much every contact that matters in the business world (unfortunately, most other data providers’ contact info contains 80% garbage, and they can’t really improve it without violating CAN-SPAM laws). LinkedIn also reflects the direction sales is heading with strong channels for thought leadership. Via LinkedIn, you can educate and advocate for your customers vs. just selling to them.

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Salesforce’s Wave Hits the Analytics Market

An op-ed I wrote for VentureBeat on why Salesforce launched Wave and the impact that will have on the analytics industry at large:

At Salesforce.com’s Dreamforce conference in San Francisco on Monday, Marc Benioff unveiled his company’s much anticipated Wave Analytics Cloud product. Marketed as “analytics for everyone” with a focus on mobility and slick visualizations inspired by video games, Wave aims to bring more analytics to decision makers more quickly.

Wave is great news for Salesforce’s massive customer base. Current customers will gain the ability to easily attain valuable insight via modern dashboards on any device, and to even execute advanced analytical operations on all types of business data. This business-intelligence (BI) approach, which appears to treat customer analytics (sales, customer support, and marketing) as a first-class citizen, is quite a departure from current horizontal BI tools like GoodData, Birst, and Tableau that focus more on performing analytics across a myriad of functions. This Salesforce Analytics Cloud is sure to deliver real business value by offering a platform that’s more specialized for customer needs, which makes sense since most use cases for BI are related to sales and customer analytics.

Why analytics is a great move for Salesforce

Anyone close to Salesforce knows that Analytics Cloud is a huge step beyond the company’s standard reporting capabilities, which have historically been rather limited. Until now, the system really just scratched the surface of a business’ sales data (try to report on something like your sales cycle lengths by lead source over time, and you’ll see what I mean). That said, it was smart of Salesforce to leave analytics up to its AppExchange partners in the beginning, because the company was busy building the SaaS world we all play in today, starting with its customer-relationship management platform. Tackling analytics at that time would have been like running two entirely different companies.

However, over the past couple years, the data needs of modern sales and marketing leaders have grown dramatically with the rise of big data. Customers are hungry for insight, and have been asking why Salesforce doesn’t offer seamless, built-in, advanced analytics. Most companies just don’t want to move data between multiple services, especially if they have rigorous security policies or huge data sets. In this data-driven environment, Salesforce’s customer satisfaction has become heavily dependent on partners it can’t control, making it increasingly important for the company to shift toward a hands-on approach to analytics and meet customers’ needs directly.

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