Atlassian launches Rovo, consolidates Jira Work Management, Jira Software

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Atlassian launched Atlassian Rovo, a generative AI assistant built on Atlassian Intelligence, which will operate across the company's teamwork platform. In addition, Atlassian said it was combining Jira Software and Jira Work Management into one project management tool.

The company announced its product updates at Atlassian Team '24 in Las Vegas.

Rovo is designed to find, learn and act on information stored across an enterprise. Atlassian Rovo is designed to surface data, understand it and deliver insights and use specialized agents to handle tasks.

With the move, Atlassian Rovo will leverage one data model, dubbed the teamwork graph, which will pull data from the company's applications and other SaaS apps. The goal is to deliver one view of goals, knowledge, actions, projects and execution.

Core components of Atlassian Rovo include:

• Rovo Search, which will comb through content wherever it is stored (Google Drive, Microsoft SharePoint, GitHub, Slack etc.), and query across applications. Rovo Search will identify team players, projects and information needed to make decisions. According to Atlassian, Rovo Search will connect niche and custom apps via API and have enterprise-grade governance to data governance.
• Insights, which are delivered via knowledge cards that offer context about projects, goals and teammates.
• Rovo Chat, a conversational bot that is built on company data and learns as it goes. Rovo will surface information and offer follow up questions.

On the backend, Atlassian Intelligence will feature generative AI in editor tools across the company's portfolio, AI-powered summaries, Loom AI workflows, virtual help center agents, AIOps and natural language AI automation rules.

• Atlassian acquires Loom for $975 million, will add asynchronous video to platform
• Constellation ShortList™ Incident Management
• Constellation ShortList™ DevOps

Constellation Research's take on Atlassian's Rovo 

Constellation Research analyst Andy Thurai received a full demo and deep dive of Atlassian's AI efforts. Here's Thurai's assessment:

"Rovo (a name designed to satisfy international customers) is primarily an enterprise knowledge and search tool. Powered by Atlassian Intelligence, you can search across Jira and Confluence for information within the platform. Currently, Rovo is limited to Atlassian and some third-party products, but you'll eventually be able to search Atlassian's marketplace. Rovo provides the contextual information that was hard to reach on the Atlassian platform before.

Atlassian uses an OpenAI private instance on the backend but has a specific agreement with OpenAI so it can’t retain the data used for prompting. OpenAI also can't use the data to train an LLM. The chatbots are currently limited only to structured data with no specific plan or timeline for unstructured data. In a demo, the chatbot had contextual awareness from Confluence and Jira and a focus on workforce productivity. 

I also liked AI summarization in the Atlassian platform. When product teams are rushed for time, employees can ask the agents to summarize the critical points without reading a bunch of lengthy documents. Rovo can create actionable items based on those documents. One customer was able to take a backlog risk analysis from two months to 20 minutes with the help of Rovo.

Rovo comes with 20+ default agents but can be extended by the customers with the no code options. Since its release few months ago, 500 internal agents have been created.

Overall, Atlassian has quietly done quite a bit of work on the AI front. Many of the new features are in beta mode so be sure to test after the full release. Atlassian focused on the system of worked and developed a bevy of capabilities. Given that competition is very limited for the knowledge worker category, Atlassian can gain traction. Atlassian's sales motion is geared toward mid-sized enterprises, but the company is trying to move up. 

Going forward, Atlassian may have to address pricing since all its go-to-market and pricing motions are geared toward large teams collaborating in an agile production cycle. With generative AI, team sizes are going to shrink. Atlassian needs to move the model away from seat-based licensing to a value-based AI-driven pricing model."

It's just Jira now

In addition to the Rovo news, Atlassian said it is taking the best of Jira Work Management and Jira Software to create one project management suite called Jira.

Jira will include goal tracking, shortcuts via AI, visualization and integrations with Confluence and Loom for knowledge sharing.

For enterprises, Atlassian said they will be able to combine SKUs and have one project management software invoice.

Atlassian added that Goals in Jira will launch in the next few months to visualize tasks and track progress to goals, Atlassian AI will break works into digestible chunks, and feature list views, calendar integration and collaboration tools.

CEO transition and earnings

Atlassian's conference kicked off a week after the company reported third quarter earnings and said it would transition to one CEO over the co-CEO model. Co-Founder Scott Farquhar will step down as co-CEO effective Aug. 31 and Mike Cannon Brookes will lead the company as CEO.

Farquhar is leaving to spend more time with his young family and philanthropy while remaining an active board member. 

The company in the third quarter reported revenue of $1.2 billion, up 30% from a year ago with net income of $12.8 million, or 5 cents a share. Atlassian said it now gets most of its revenue from its cloud products and has 300,000 customers on its cloud. Non-GAAP earnings for the third quarter were 89 cents a share.

For the fourth quarter, Atlassian projected revenue between $1.12 billion to $1.13 billion with cloud revenue growth of 32%.

Brookes said, "we're incredibly bullish about AI" and the scale across the Atlassian platform is "one of the areas that I always think is underestimated in terms of durable growth and in terms of long-term advantage."

CFO Joe Binz said Atlassian is navigating a mixed demand picture. On the third quarter earnings conference call, Binz said:

"Enterprise was healthy across both cloud and data center and that drove the record billings, strong growth in annual multiyear agreements. Strong migration and good momentum in sales of premium and enterprise additions of our products will roll through our revenue results.

The macro impact on SMB, on the other hand, continued to be challenging, although also in-line with expectations. And that macro headwind in SMB lands primarily in cloud, given SMB makes up a significant part of that business."

Anthropic launches Claude Team plan, iOS app

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Anthropic said it will launch a Team plan and iOS app for its Claude large language model for $30 a month with a minimum of five seats.

With the move, Claude will compete with OpenAI's ChatGPT plans. Microsoft and Google both have apps for Copilot and Gemini, respectively.

Anthropic's Team plan will give teams a workspace and tools for managing users and billing. The Claude iOS app features the Claude 3 model family, sync chat history and support photos.

• Anthropic CEO Amodei on where LLMs are headed, enterprise use cases, scaling
• AWS ups its investment in Anthropic as giants form spheres of LLM influence
• Foundation model debate: Choices, small vs. large, commoditization

Key items about the Team plan:

• The Team plan has more usage per user than the Pro plan and access to all of the Claude models including Opus, Sonnet and Haiku.
• A 200,000 token context window to process long documents and have multi-step conversations.
• Admin tools and billing management.
• All of the features in Claude Pro.

AMD Q1 delivers data center, AI sales surge of 80%

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

AMD reported better-than-expected first quarter earnings largely due to strong data center growth and the ramp of the company's MI300 AI accelerator.

The company reported first quarter earnings of $123 million, or 7 cents a share, on revenue of $5.5 billion. Non-GAAP first quarter earnings were 62 cents a share.

Wall Street was expecting AMD to report first quarter earnings of 61 cents a share on revenue of $5.45 billion.

AMD is critical as a second supplier for AI processors and GPUs as enterprises and cloud providers spend heavily on Nvidia. Here's the current state of AI chip players:

• Intel launches Gaudi 3 accelerator with availability in Q2
• Intel Q2 outlook weaker than expected
• Nvidia Huang lays out big picture: Blackwell GPU platform, NVLink Switch Chip, software, genAI, simulation, ecosystem
• Will generative AI make enterprise data centers cool again?
• AWS presses custom silicon edge with Graviton4, Trainium2 and Inferentia2

Lisa Su, AMD CEO, said the "widespread deployment of AI is driving demand for significantly more compute across a broad range of markets. We are executing very well as we ramp up our data center business and enable AI capabilities across our product portfolio."

As for the outlook, AMD projected second quarter revenue of $5.7 billion, give or take $300 million.

By unit, AMD posted record data center revenue in the first quarter of $2.3 billion, up 80% from a year ago. Growth was driven by AMD Instinct GPUs and 4th Gen AMD EPYC CPUs. The PC unit had first quarter revenue of $1.4 billion, up 85% from a year ago. Gaming revenue was $922 million, down 48% from a year ago. Embedded revenue in the first quarter was $846 million, down 46% from a year ago.

On an earnings conference call, Su said server CPU sales were strong in a seasonally down first quarter due to "growth in enterprise adoption and expanded cloud deployments."

She said there are nearly 900 AMD powered public cloud instances across hyperscalers.

Regarding AI, Su said:

"In the enterprise, we have seen signs of improving demand as CIOs need to add more general purpose and AI compute capacity while maintaining the physical footprint and power needs of their current infrastructure."

She added that MI300 is the fastest ramping product in AMD history and has passed $1 billion in total sales in less than two quarters. "We now expect data center GPU revenue to exceed $4 billion in 2024, up from $3.5 billion we guided in January," said Su. "Longer term, we're increasingly working closer with our Cloud and Enterprise customers as we expand and accelerate our AI hardware and software roadmaps and grow our data center GPU footprint."

She added:

"AI represents an unprecedented opportunity for AMD. While there has been significant growth in AI infrastructure build outs, we're still in the very early stages of what we believe is going to be a period of sustained growth driven by an insatiable demand for both high performance AI and general-purpose compute."

Su also was bullish on prospects for AMD's Ryzen processors and AI PCs with additional market share gains in commercial accounts.

AWS annual revenue run rate hits $100 billion as growth accelerates

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Amazon Web Services revenue growth accelerated in the first quarter as the cloud giant reported sales of $25 billion.

Amazon reported overall first quarter net income of $10.4 billion, or 98 cents a share, on revenue of $143.3 billion, up 13%. Wall Street was expecting Amazon to report earnings of 83 cents a share on revenue of $142.56 billion.

With the Amazon and AWS results, it's clear that hyperscale cloud providers are landing AI workloads. Microsoft Azure revenue in Q3 up 31% | Alphabet shows Q1 strength in Google Cloud, initiates dividend

AWS delivered first quarter operating income of $9.4 billion on revenue of $25 billion, up 17% from a year ago. Fourth quarter revenue growth for AWS was 13%. Wedbush was expecting AWS first quarter revenue of $24.6 billion. AWS announced the general availability of Amazon Q earlier in the day. 

By the numbers:

• Amazon's North America commerce unit had first quarter revenue of $86.3 billion with operating income of $5 billion.
• International commerce sales in the first quarter were $31.9 billion, up 10% from a year ago, with operating income of $900 million.
• Amazon's first quarter net income includes a $2 billion non-operating loss from the company's investment in Rivian.
• Amazon advertising revenue in the first quarter was $11.8 billion, up 24% from a year ago.

CEO Andy Jassy said AWS was benefiting from "the combination of companies renewing their infrastructure modernization efforts and the appeal of AWS’s AI capabilities is reaccelerating AWS’s growth rate (now at a $100 billion annual revenue run rate)."

Speaking on an analyst conference call, CEO Jassy talked up cloud demand, Amazon Bedrock and the company's approach to generative AI. He said: 

"Companies have largely completed the lion's share of their cost optimization and have turned their attention to newer initiatives. We see considerable momentum on the AI front where we've accumulated a multi billion dollar revenue run rate already."

Jassy touted Bedrock and said enterprises are increasingly looking at generative AI strategies that revolve around model selection and customization ability. He said Bedrock's recent launch of custom model import was "a sneaky launch as it satisfies a customer request that has not been met yet." Amazon Bedrock gets custom model import, evaluation tools, new Titan models

• Amazon CEO Jassy's shareholder letter talks AWS' approach to generative AI
• AWS' Matt Wood on model choice, orchestration, Q and evaluating LLMs
• AWS ups its investment in Anthropic as giants form spheres of LLM influence

"The prospect of these two linchpin services in SageMaker and Bedrock working well together is quite appealing the top of the stack for the Gen AI applications being built," said Jassy, who added that Q is off to a good start with enterprises. 

He said capital spending will be up as AWS builds out data centers to meet demand. 

"The more demand AWS has, the more we have to procure new data centers power and hardware. And as a reminder, we spend most of the capital upfront. As you've seen over the last several years, we make that up an operating margin and free cash flow down the road as demand scales out. We don't spend the capital without very clear signals that we can monetize it. We remain very bullish in AWS. We're at $100 billion dollar annualized revenue run right now and 85% or more of the global IT spend remains on premises. And this is before you even calculate genAI.  There's a very large opportunity in front of us."

As for the outlook, Amazon projected second quarter sales of $144 billion to $149 billion, up 7% to 11% from the previous year.

More:

• AWS Q4 revenue growth 13% as Amazon's results shine
• Amazon Generative AI Stack Offering Overview
• Amazon's Vogels says 'cost awareness is a lost art' as AWS launches optimization tools
• These overlooked AWS re:Invent launches could solve pain points
• AWS launches Amazon Q, makes its case to be your generative AI stack

Amazon Q generally available with new pricing plans

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Amazon Q is generally available across the Amazon Web Services ecosystem and the generative AI capabilities come with new pricing models.

AWS' Q generative AI assistant was announced at re:Invent and has been tested across multiple use cases before availability. Amazon Q is a layer in the AWS stack that serves as glue across multiple services.

The headliners for Amazon Q are Amazon Q Developer, a coding assistant, Amazon Q Business, designed to make employees more productive, and Amazon Q Apps, which are part of Amazon Q Business and can automate business tasks. Amazon Q Apps are in preview. 

As for pricing, Amazon Q Business has two tiers. Amazon Q Business Lite is $3 per user a month for basic functionality. Amazon Business Pro, which includes all features, Amazon QuickSight and Amazon Q Apps, goes for $20 per user a month.

Amazon Q Developer has a free tier and Pro, which is $19 per month per user.

AWS has a few pricing examples. Here's one for Amazon Business.

You are an enterprise company with 5,000 employees looking to deploy Amazon Q Business. You decide to purchase Amazon Q Business Lite for 4,500 users and Amazon Q Business Pro for 500 users. You have 1 million enterprise documents across sources like SharePoint, Confluence, and ServiceNow that need indexing with an Enterprise Index. Your monthly charges will be as follows:

• Enterprise Index for 1M documents will need 50 index units of 20K capacity each (assuming that the extracted text size of 1M documents is less than 200 MB * 50 units = 10 GB) :
• $0.264 per hour x 50 units x 24 hours x 30 days = $9,504

User subscriptions:

• 4,500 users * $3 per user/month = $13,500
• 500 users * $20 per user/month = $10,000
• Total user subscriptions: $23,500

In summary, your monthly charges are as follows:

• Enterprise Index: $9,504
• User subscriptions: $23,500
• Total per month: $33,004

The return-on-investment case for Amazon Q is straightforward--Amazon Q will provide a productivity boost. Amazon Q Developer also has tools to optimize their AWS environments by analyzing billing trends, consumption and costs by region.

Amazon Q Business is able to connect to more than 40 common business tools to surface insights and serve up insights and dashboards on the fly.

More:

• Amazon CEO Jassy's shareholder letter talks AWS' approach to generative AI
• AWS' Matt Wood on model choice, orchestration, Q and evaluating LLMs
• AWS ups its investment in Anthropic as giants form spheres of LLM influence
• AWS Q4 revenue growth 13% as Amazon's results shine
• Amazon Generative AI Stack Offering Overview
• Amazon's Vogels says 'cost awareness is a lost art' as AWS launches optimization tools
• These overlooked AWS re:Invent launches could solve pain points
• AWS launches Amazon Q, makes its case to be your generative AI stack

Coursera's outlook highlights how genAI reskilling will be lumpy

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

The state of reskilling in the generative AI era looks like it's going to be a bit lumpy if Coursera's first quarter results and outlook are any indication. Coursera CEO Jeff Maggioncalda said, "we remain in the early stages of understanding how generative AI will reshape the way we live, learn and work."

Coursera's first quarter results were mixed as earnings beat expectations, but revenue fell short. The second quarter outlook from Coursera calls for revenue of $162 million and $166 million, well below Wall Street estimates of $177.8 million. Coursera said 2024 revenue will be $695 million to $705 million, which was short of $736.5 million.

The company has three operating units--consumer, enterprise and degrees. Consumer revenue was up 18% in the first quarter compared to a year ago and enterprise and degrees revenue was up 10%. AI courses were driving demand in consumer and building in enterprise and degrees. Coursera's generative AI transformation is about a year old. 

• Why you need to connect your hiring to data, outcomes pronto
• Education gets schooled in generative AI
• Accenture goes big on AI reskilling, acquires Udacity, launches LearnVantage
• 7 future of work themes to know now

However, for all the talk of reskilling in the genAI era there are false starts. Citing an Accenture report, Maggioncalda noted that 95% of employees see value in working with generative AI, but only 5% of organizations are actively reskilling their workforce at scale.

For a company like Coursera, the challenges are leveraging genAI for content creation in an accurate way, being able to swap models as needed and hitting learnings beyond builders. Coursera has built out its AI courses and landed deals with enterprises as well as universities.

Maggioncalda said Coursera partners have built out more than 75 new courses and project in generative AI since the start of the year. Coursera is also using generative AI to power Coursera Course Builder that will enable "any business, government or campus customer, to easily and quickly produce high-quality custom private courses at scale."

In addition, Coursera Coach is designed to be an AI-powered tutor. So, what's the problem? Here are a few.

• Consumer revenue. Ken Hahn, CFO of Coursera, said consumer revenue "was softer than anticipated" in North America. "We underperformed in our North American region, where we are experiencing a lower volume and conversion of paid learners compounded by the delay of the key content launch from one of our educator partners as compared to the timing in our financial plan," said Kahn.
• Businesses are mixed when it comes to reskilling. Government and campus verticals are showing strong demand for Coursera for Business, but corporate learning budgets are tight. "We continue to see a divergence in performance across our verticals, specifically pressuring Coursera for Business, offset by momentum in our other two verticals, government and campus," said Kahn. "Corporate learning budgets remain under pressure."
• The degree revolution hasn't arrived just yet. Coursera's degree revenue was $14.8 million in the first quarter, up 10% from a year ago. Total number of students was 22,200, up 23% from a year ago. There are no content costs for degree revenue, so the segment sees gross margins of 100% of revenue. Kahn said:

"We remain focused on the long-term opportunity in degrees. We believe that our platform is uniquely positioned to fundamentally transform the college degree. We need to start validating that potential with renewed and increasing growth. We believe that the path to better degrees growth lies in working with our university partners to create stronger pathways between our consumer segment where we benefit from scale and the growing selection of pathway degree programs."

Maggioncalda said AI content is driving engagement, but there needs to be more courses that cater to a larger base. He said:

"People want new AI content, both for the builders who are building these models. But also, the users, people who need to learn how to use this stuff. We see broad appetite 4x what we saw last year in terms of people taking AI-related content."

Ultimately, the population of AI users is going to be much larger than the builders. Coursera needs to accelerate content launches that add AI throughout existing courses and launch modules that educate people on how their roles will change.

Maggioncalda said:

"Generative AI will have a huge impact on the way people do their jobs.

They're going to need to learn new skill to be, you name it, a PR comms person or a financial analyst or a supply chain manager or a UX designer. We think there's a very broad opportunity to really refresh the content to appeal to strong demand that we're seeing from learners around generative AI."

Snapchat gets boost from lower cloud infrastructure costs

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Snapchat made a bet on using machine learning and AI to improve its advertising platform, increase content engagement and ultimately revenue growth. If it could optimize its infrastructure spending, Snapchat would be able to grow the bottom line.

The first quarter gave an indicator that Snapchat's bets are starting to pay off. What's unclear is whether the company can continue to optimize its cloud spending since the first quarter bottom line was helped along by credits from hyperscale cloud providers.

Google Cloud is Snapchat's primary cloud provider, but Amazon Web Services is in the mix, according to Snapchat's regulatory filings.

CFO Derek Anderson said:

"We benefited from higher-than-average service provider credits in Q1 that helped to further reduce infrastructure costs in Q1. As a result, infrastructure cost per DAU declined from $0.84 in Q4 of 2023 to $0.80 in Q1 of 2024."

Saving 4 cents per daily active user doesn't sound like much until you scale those savings across 422 million daily active users. In Snapchat's results, cloud costs--operating expenses--turn up in cost of revenue. Snapchat executives said on the company's first quarter earnings call that the company is spending about $100 million a quarter on machine learning and AI.

"CxOs need to consider that cloud infrastructure costs are driven by usage, no matter how efficient an application's usage of the infrastructure is," said Constellation Research analyst Holger Mueller. "So for Snapchat shaving infrastructure cost is a step in the right direction – but not an insight on the efficiency of its coding."

The company reported a net loss of $305.1 million, or 19 cents a share, on revenue of $1.19 billion, up 21% from a year ago. Non-GAAP earnings were 3 cents a share, well above expectations.

Snapchat CEO Evan Spiegel said in a shareholder letter and the earnings call that the company is improving content ranking and personalization with the help of its AI investments.

"We've built larger and more advanced ranking models that are driving improvements in content engagement. In addition, we made significant progress toward unifying the ranking models between Spotlight and Stories to a single backend stack that ranks all content types," said Spiegel. "A single, unified stack will benefit Snapchatters by showing them the most relevant and entertaining content across Snapchat and helping creators find and deepen engagement with their audience."

An improving ad market also helped Snapchat, but its cloud savings flowed faster to the bottom line. Snapchat noted that it has improved its cloud infrastructure unit costs with "engineering efficiency and pricing improvements."

Indeed, Snapchat was an active participant in Google Cloud Next with sessions on moving to a microservices architecture and how it is using BigQuery and other data platforms. Snapchat has been built on Google Cloud since its inception and participated in 10 sessions at Google Cloud Next.

However, Snapchat said quarterly costs per daily active user (DAU) will be in the 83 cents to 85 cents range for the remainder of 2024. It's worth noting that Snapchat had an infrastructure cost per daily active user of 59 cents in the first quarter of 2023 and 70 cents due to its AI investment in the second quarter of 2023 before escalating to current levels of 80 cents to 85 cents per DAU.

Snapchat's infrastructure cost per DAU guidance seems to indicate that the company still has to work on its cloud optimizations and account for its AI investments. It's possible that the first quarter cost of revenue was helped in a large part because of one-off cloud credits.

Fully optimized--assuming infrastructure costs from 2022 are a benchmark--Snapchat's optimized state is infrastructure costs of 59 cents per DAU.

Spiegel said that infrastructure costs are slowing quarter over quarter as the company optimizes its spend even as it boosts revenue growth. 

A neutral vendor in your stack is great, but also a pipe dream

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Every enterprise technology stack needs neutral vendors that play well with others, integrates seamlessly and keeps customer value front and center while refraining from the dreaded cross-sell.

The problem is that these neutral vendors are acquired if they become too successful. Once these neutral vendors are acquired it's all about the cross-sell game under new ownership.

We had a near miss recently with Informatica. Informatica has a data management platform that connects with all the primary clouds and enterprise systems. As businesses look to adopt generative AI, they're increasingly realizing that a vendor like Informatica is a go-to player.

Informatica was doing well being Switzerland that Salesforce reportedly wanted to buy it. Talks broke down and Informatica remains a neutral party--for now.

There are a bevy of neutral vendors considering regulators around the world are a hard sell on mergers and acquisitions. At some point that'll change. There are already signs that the M&A market will accelerate.

This post first appeared in the Constellation Insight newsletter, which features bespoke content weekly and is brought to you by Hitachi Vantara.

It's possible that HashiCorp looked like a neutral vendor across clouds, but it has now been acquired by IBM in a $6.5 billion deal. IBM is an example of a company that has played the neutrality game and scaled. IBM has morphed repeatedly over the years, but the combination of AI and consulting are strong. Keep in mind that IBM also acquired Red Hat, which has kept most of its neutrality cred.

When conditions change vendor neutrality will become a bit of a pipe dream. Consider VMware. VMware was neutral across data center infrastructure and connected clouds. Now that VMware is part of Broadcom, customers are antsy about lock-in and the transition to subscriptions over licenses. Nutanix gets the neutrality sales pitch--until it's acquired.

I'd argue ServiceNow is a version of a neutral play as it can build workflows and processes on top of multiple systems of records. However, ServiceNow dependence also means higher prices at some point, but hopefully there's value too. "We're not interested in shutting anybody out. We're actually technology capable enough to open up to everybody and that's really turning on the whole ecosystem in our favor," said ServiceNow CEO Bill McDermott, speaking on the company's first quarter earnings call.

When it comes to large language models (LLMs), AWS obviously wants to be your Switzerland of generative AI. Google Cloud will also play that game. Microsoft will speak to it, but for now is closely affiliated with OpenAI. Hugging Face is your neutrality play but could be acquired down the line.

Celonis is another company that's neutral and can tap into multiple systems for process intelligence. It might grow into an IPO--or become part of a larger vendor. UiPath is in a similar automation and process bucket. There are plenty of other neutrality options including Atlassian, Nvidia and data platforms such as Snowflake, MongoDB and DataBricks.

Bottom line: Chances are that your neutral vendor today will not remain that way 5 years from now. CIOs can manage the vendor neutrality dream if they play along early and then keep their options open. The biggest lesson from the Informatica cadence is that neutrality can be successful, but eventually it's a pipe dream.

Also:

• Enterprises Must Now Cultivate a Capable and Diverse AI Model Garden
• Secrets to a Successful AI Strategy
• Return on Transformation Investments (RTI)

SoundCommerce CEO Eric Best: 'Data capability enables customer lifetime value'

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

SoundCommerce Co-Founder and CEO Eric Best said retail winners will increasingly be determined by how they leverage data and artificial intelligence to drive customer lifetime value.

Best, along with CTO Jared Stiff started the company to help brands deliver better shopper experiences with data. SoundCommerce, founded in 2018, has raised more than $33 million in funding. The company platform is designed to take retail data infrastructure and make it composable and no code so retailers can better model experiences on the fly.

Retailers will need to leverage data to thrive amid margin compression, pricing arbitrage, higher cost of capital and fierce competition. On DisrupTV, Constellation Research's Ray Wang and Holger Mueller caught up with Best. Here are some of the key takeaways. 

Two megatrends impacting retail. Best said there are two obvious megatrends that are reshaping retail. The first is the return to shopping in person and retail as a community activity. The second is that the cost of capital has increased dramatically. Both are impacting direct-to-consumer retailers.

Best said of direct-to-consumer retail:

"There are high variable costs on the front end to acquire a customer through some combination of Facebook, Tik Tok, Instagram and Google and on the other end, there are very high costs associated with doorstep delivery. We often joke internally that there are a thousand things that must go right to be successful in digital retail. And you fail if any one of them goes wrong."

Best of times, worst of times. Best said it is easier than ever to start a retail business because of platforms like Shopify and marketplace providers like Amazon and Walmart. "Getting started is very easy. Anyone can throw up a shingle," said Best. "Scaling the business is hard and profitable growth is exceedingly difficult."

Because of this difficulty you see direct-to-consumer brands like Casper, Warby Parker and Dollar Shave Club to back to omnichannel, wholesale and physical stores. "The market is proving that these are difficult businesses to operate," said Best.

Who owns the customer? Best added that there are trade-offs between following a direct-to-consumer model vs standing up for business in a marketplace. For instance, if you're an Amazon seller much of the complexity of the business model is removed once you figure out how to promote your products.

The trade-off happens when the marketplace owns the customer and experience as well as the data, which is "a really important asset to the enterprise value of consumer brands," said Best. "It is rare to see companies that are able to rely on a marketplace," he added.

Feedback loops. Data is critical because digital commerce requires a lot of data, analytics and insights to power the next best actions and feedback loops. Best said he expects data platforms to become more important to retail. "We have a proliferation of brand-new companies building data capabilities on the backs of Snowflake or Google Cloud or DataBricks," said Best.

Best said Amazon is a great example of retail as data feedback loop. AWS was created as a proprietary infrastructure for predictions, modeling inventory and logistics based on demand signals. "The use cases we see emerging wit generative AI began with proprietary algorithms that were developed by Amazon or Walmart," said Best.

The SoundCommerce bet. Best said SoundCommerce is scaling on two core constructs. First, every retail business decision has the potential to be a generative AI prediction that can be tactical as well as strategic. And then there's the data capabilities that can be game changers. "We think data capability enables customer lifetime value. There's a connection of individual tactical decisions that can be tied together to drive long-term customer relationships," said Best.

Data management will be mission critical for retailers since the biggest barrier to AI adoption isn't the algorithm, but having the data cleaned and properly structured for AI consumption. SoundCommerce has a set of models for omnichannel, acquisition and retention marketing, products and promotions and fulfillment. "The challenge we see across industries is readiness and the heavy lifting to get the data ready in the first place," said Best.

More:

• Shopify eyes offline, B2B markets for commerce growth
• Extend ramps as retailers eye extended warranty, shipping protection plans
• Blue Yonder acquires One Network for $829 million
• Walmart, Target highlight intersection of supply chain, customer experience
• Amazon vs. Walmart: 8 innovation takeaways
• BT150 interview: Wayfair CTO Fiona Tan on transformation, business alignment and paying down tech debt
• How Wayfair’s Tech Transformation Aims to Drive Revenue While Saving Money
• How Home Depot blends art and science of customer experience