5 Marketing Mistakes that Database Providers Make—And How to Fix Them
Too much left-brain thinking results in jargon and a narrow focus, to the exclusion of bigger opportunities
We expect perfection from database providers—no data loss, no errors, 99.999% availability—but we don’t always get it.
This is especially true in PR & Marketing, where I’ve had first-hand experience as a tech journalist, analyst, and employee of three of the leading database vendors—Oracle, IBM, and MongoDB.
I have worked with with the CEOs, CMOs, CTOs, and Chief Communications Officers at more than a dozen database companies, and I know good communications, marketing, and messaging when I see it. And I can see the missteps as well.
Who’s getting it right? Here are a few examples.
AWS does a great job with the keynote presentations at its re:Invent conference.
Snowflake sets itself apart by showcasing customers and with its focus on data clouds and a data marketplace.
Google Cloud’s subject matter experts (SMEs) are fantastic—knowledgeable, plain-spoken, accessible.
Cockroach Labs aligns its value proposition—survivability—with the industry’s most unique name.
But this post is about the opposite of good comms and marketing. It’s about hype, jargon, miscues, missed opportunities, and sending the wrong message to the wrong audiences through the wrong channels.
In the database market, the “narrative” is overly focused on just two things: One, features and capabilities. And two, the developer audience.
Those are important, of course, but the risk is that database companies begin to sound the same. Or worse, they lose mindshare and/or marketshare because we lose interest in what they are saying and doing.
Here are a five examples of what I’m talking about.
1. Too Much Jargon
A lot of the language of data management is created by technologists for technologists. That’s a reasonable starting point, but too often it results in an alphabet soup of technical terms that are incomprehensible to others.
Here is a sampling of terms from database websites that I just visited: FIPS, OAuth2, Node, ACID, Paxos, subcluster, JDBC, ODBC, HDFS, QLDB, TLS, PartiQL, A2, C2, E2, C2D, T2D, UDF, sparse multi-dimensional arrays, vectors, non-materialized integer dimension, columnar, multi-model/modal, dedupe, SOC 2 Type II, NLP, convolutional neural networks, parallelize, VCF, and LAZ. (I had to look up LAZ, which is a file extension for LiDAR data.)
It’s easy to see why this happens. Database, analytics, ETL, and other vendors are all trying to win the attention of the technical user base. That makes sense, but they need to remember that there’s a broader potential audience out there.
2. Narrowly Focused on Audience
One way to fix the techno-jargon problem is to target a wider audience with a more comprehensible message about business impact, not just software nitty-gritty.
Developers and data engineers may be the right core audiences, but it’s a mistake to focus too narrowly. There’s a growing universe of non-technologists who care about data management—everyone from college students to “citizen data scientists” to CEOs interested in leveraging real-time analytics.
When I worked as an editor at InformationWeek magazine, we cast the net wide to include business & technology decision makers. There was a lot of blurring of the lines—technical people with business responsibilities, business people with technical oversight, and everything in-between.
Here at the Cloud Database Report, the job titles of subscribers include Client Lead, Consultant, Business Development, VP of Strategy, Cloud Business Leader, and Pre-sales, to name a few.
Most database companies would love to reach people like that. They might be very interested in knowing how vector databases, operational analytics, streaming data, and other leading-edge capabilities could give them a competitive advantage. It’s a mistake to overlook them.
3. Badmouth the Competition
Earlier in my career, there was a lot of smack talk in the tech industry. Sun Microsystems CEO Scott McNealy once called the Windows OS a “giant hairball” and alluded to Microsoft’s top two execs as “Ballmer and Butt-Head,” according to an old ZDNet article.
These days, there’s not as much name calling, and for good reason. In a multi-cloud world, competitors must be able to play nice because customers want to mix and match technologies without all the drama.
The big rivalry that continues to draw pointed barbs is Oracle vs. AWS. Of course, that comes at a cost, as Oracle learned when Amazon's consumer business ditched 7,500 Oracle databases.
I’m surprised when I see other database companies jump into the mud like this. MongoDB continues to aggressively square off against Amazon DocumentDB, as you can see from this webpage: “Amazon DocumentDB is 33.96% compatible — it fails 941 of 1,425 MongoDB core compatibility tests.”
This is a head-scratcher given that MongoDB and AWS recently announced an expanded strategic agreement, and MongoDB has signed on as an Emerald Sponsor of AWS re:Invent 2022.
4. Timidity
Too often database companies decline to comment on things that matter. Recently, I have found it challenging to get people on the record for reporting I’ve done on gun reform or the war in Ukraine, both of which have noteworthy data-management angles.
And Microsoft refused an opportunity to discuss the scalability of Azure SQL Server. I invited Microsoft to share an update on SQL Server for a feature article I wrote on the anniversary of “Scalability Day,” a major event that Microsoft hosted 25 years ago.
Here’s the story, without any input from Microsoft.
Microsoft’s reticence left the impression that it was being evasive, which was reinforced by subsequent headlines like this one from The Information: “Microsoft Cloud Computing System Suffering from Global Shortage.”
The thing for these companies to remember is that “no comment” seldom carries a neutral connotation. We are left to wonder what the true story is and why.
5. Lack of Creativity
Perhaps the biggest marketing challenge that data companies face is that their messaging is too bland and predictable.
This is not surprising when you consider how many left-brain types are running these companies. I recently talked to the CEO of a cloud database company who lamented the old-style thinking that continues to dominate industry conversations.
Database companies must be able to differentiate and separate themselves from the pack. The way to do that is to reveal what’s new, different, interesting, and innovative. As I noted earlier, Snowflake has been one of the most successful at recasting the conversation in a way that resonates with a broader audience.
Snowflake talks about data warehouses without talking about data warehouses!
True thought leadership is a way to break away from the same old rote soundbites. Here are a few examples of companies that are figuring out how to do that:
TileDB - Founder and CEO Stavros Papadopoulos has thought-provoking ideas on what he calls “the new data economics.”
SingleStore - Talks about the five dimensions of “data intensity” and introduced a calculator that customers can use to gauge this metric themselves.
Ocient - Laser focused on managing “the world’s largest datasets” and hyperscale data analysis.
Break the Mold
I have grappled with every one of these issues myself as a content and communications strategist.
There’s no single or simple answer. Yet, not only is it possible for cloud database companies to distinguish themselves in a crowded market—it’s essential for market leadership.