Aprimo’s Acquisition Of ADAM Software Signals Market Consolidation

Nick Barber
Marketing resource management (MRM) vendor Aprimo snatched up ADAM Software, which bolsters Aprimo’s digital asset management (DAM) capabilities and reinforces the consolidation and convergence that we predicted. 
 
There are a lot of small DAM vendors, but there has been a move to consolidate. Specifically, the capabilities of MRM, DAM, and content marketing platforms (CMP) continue to blur. MRM vendors like Aprimo help marketers assign tasks, track resources, budget, and review materials. But they stop short of organizing large libraries of content, integrating with upstream creative workflows, and delivering content downstream. The clear benefit of this merge is that now marketers will have one solution across the entire content lifecycle. 
 
Other large vendors in the market have taken a similar approach. Adobe has built out its offering to include DAM, web content management (WCM), analytics and other capabilities. Multinational conglomerate Danaher purchased MediaBeacon to merge under product-packaging software vendor Esko. Shutterstock bought WebDAM to give Shutterstock a viable story for stock image management.
 
ADAM’s purchase comes as no surprise. Their strength in DAM, noted in our Forrester Wave, and relatively small size made them an attractive acquisition target. 
 
What does Aprimo’s acquisition of ADAM mean for the market?
 
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Customer Success Should Be A Team Sport

Kate Leggett

Customers hold the power in their relationships with businesses. Today, it's not enough for businesses to deliver products. Customers expect them to deliver outcomes and success.

To do this, businesses must understand who the customer is, what their pain points are in achieving their business goals, and must help them choose the right products to meet their goals. The relationship does not stop there. Businesses must ensure that a new customer is properly onboarded, and is realizing ongoing value from their purchase. Forrester data backs these statements up. 68% want vendors who “understand my business, my problems – and help me solve them.”

This is the mission of customer success teams. They actively manage customers post-purchase, to ensure their ongoing success, with the end goal of reducing churn, increasing customer lifetime value and advocacy - the latter of which influences new sales.

Most businesses pursue this mission by standing up customer success organizations. They use a health score  — comprised of financial data, CRM data, product usage data, support cases, customer feedback  — to track their customers. However, most company employees interacting with customers don’t have this visibility into a customer’s health which can impact overall relationships.

Totango, a vendor of customer success solutions, has a very different view of customer success. Sure customer success teams manage overall customer relationships. However, Totango believes that everyone interacting with customers must have access to customer data and their health in order to better engage with them. Employees must also be able easily, with little friction, access this information from within the context of their application.

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Fourteen Machine Learning Solutions For Data Scientists - Which One Is Best For You?

Mike Gualtieri

Yogi Berra, Machine Learning For Predictive ModelsThe Power To Predict Is Mighty

Yogi Berra once said, "It's tough to make predictions, especially about the future." It is tough indeed, but enterprises that can make probabilistic predictions about customers, business processes, and operations will have an edge over enterprises that can't. These predictions don't have to be macroscopic to be consequential. Predictions about what a customer is likely to buy next. Predictions about marketing content that will resonate with a prospect. Predictions about the next best action to take in a business process. Predictions about when an expensive asset is likely to break down. Virtually any customer journey, business process, and even strategic decision can be made better if permeated with the power to predict.

Predictive Analytics And Machine Learning Solutions Make It Possible

Yes, making accurate predictions is tough, but predictive analytics and machine learning (PAML) solutions provide data scientists and developers alike with the tools to make it happen. Forrester defines PAML solutions as:

Software that provides data scientists with 1) tools to build predictive models using statistical and machine learning algorithms and 2) a platform to deploy and manage predictive production models.

The Forrester Wave™: Predictive Analytics And Machine Learning Solutions, Q1 2017

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Introducing The New NTT DATA

Liz Herbert

This week, NTT DATA brought together a select community of industry and financial analysts to introduce the new NTT DATA, following the recent acquisition of Dell Services. Though not a well-known brand to most, NTT DATA wants to change that and has launched a series of new campaigns to run on TV and in major publications such as The Economist.

This $4.3B+ services firm is a rollup of many acquisitions including Keane, Carlisle and Gallagher Consulting Group, Optimal, Intelligroup, Centerstance, and most recently Dell Services (which included the erstwhile Perot Systems) -- and forms the largest operating company of Japan-based NTT DATA Corporation. The provider's capabilities span consulting and technology implementation and support, including SAP and Oracle and Salesforce services. NTT DATA is strongest in healthcare and life sciences, financial services, manufacturing, and public sector. NTT DATA boasts clients all around the globe – from Japan to the US to Western Europe and beyond.

NTT DATA has a unique and leading partnership with Dell (due to the Dell Services acquisition) and has a network of companies in the broader NTT Group such as DOCOMO, Dimension Data, and NTT Comms – that it can seamlessly leverage for mobile, data center, and network needs. For example, NTT DATA has collaborated with NTT Communications and Dimension Data when clients seeks a broader range of hosting and infra services related to SAP HANA deployments. NTT Group also has substantial investments in R&D and innovation including in advanced technologies such as sensors and voice recognition and holograms, which NTT DATA can bring to bear for clients.

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Don’t Be Fooled -- DAM Is Still Relevant

Nick Barber
If you think digital asset management solutions are a relic of the past or a graveyard of static assets then you’re dead wrong. While complementary technologies like web content management, content marketing platforms, and product information management offer DAM-like capabilities, most marketers still prefer to use a dedicated DAM.
But how do you determine if you need a dedicated DAM or if you can use adjacent technologies to store your rich media assets? That’s exactly what we answer in Eight Questions To Consider When Investing In Digital Asset Management.
 
Keep in mind these key considerations when weighing a DAM investment:
 
  • DAM can serve as the central hub for your content. DAM solutions of today sit squarely between upstream creative workflows and downstream delivery mechanisms. If you have multiple systems that need to access rich media content, a dedicated DAM is the core repository that serves that content into a presentation layer. 
 
  • DAM supports complex workflows and multiple stakeholders. DAM systems have integrated components of marketing resource management (MRM) technologies around planning and allocation of resources. DAM allows your team to pass around an asset for creative and legal approval. Each stakeholder can annotate assets and review iterations before creative teams finalize assets. 
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Five Shades Darker? – What The Diageo “Indirect Access” Judgement Really Means For SAP Customers

Duncan Jones

At last, exactly two years later, the long-awaited sequel to my hit, if overly censored, blog post: Five Shades Of Grey (How software buyers and license managers should be compliant without being submissive). The trigger is the SAP vs Diageo verdict, which generated a lot of hysterical blogging and tweeting with dire predictions for SAP customers. IMO most commentators have overlooked the crucial parts of the judgment and therefore significantly overstated the case’s negative implications for SAP customers. I believe the judgement has actually made this grey area slightly more black-and-white. My analysis, subject to the usual IANAL disclaimer, is that the real implications are:

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What Exactly The Heck Are Prescriptive Analytics?

Mike Gualtieri

Prescriptive analyticsPrescriptive analytics is about using data and analytics to improve decisions and therefore the effectiveness of actions. Isn’t that what all analytics should be about? A hearty “yes” to that because, if analytics does not lead to more informed decisions and more effective actions, then why do it at all? Many wrongly and incompletely define prescriptive analytics as the what comes after predictive analytics. Our research indicates that prescriptive analytics is not a specific type of analytics, but rather an umbrella term for many types of analytics that can improve decisions. Think of the term “prescriptive” as the goal of all these analytics — to make more effective decisions — rather than a specific analytical technique. Forrester formally defines prescriptive analytics as:

"Any combination of analytics, math, experiments, simulation, and/or artificial intelligence used to improve the effectiveness of decisions made by humans or by decision logic embedded in applications."

Prescriptive Analytics Inform And Evolve Decision Logic Whether To Act (not not act) And What Action To Take

Prescriptive analytics can be used in two ways:

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Scifi Version Of AI Is Not Available Yet

Mike Gualtieri

Spark Summit East came to Boston this year and I was there to enjoy it including being interviewed by Dave Vallente and George Gilbert about Apache Spark and AI on The Cube. We talk about the waning of the term "Big Data" , but get quickly into the future of AI and Apache Spark.

Get ready for Business Intelligence market next wave of M&A

Boris Evelson

Business intelligence (BI) is a runaway locomotive that keeps picking up speed in terms of enterprise interest, adoption, and spending levels. The result: Forrester now tracks 73(!) vendors in the segment. Their architectures and user interfaces vary, but they support similar use cases. Forrester started the original research with fewer than 30 vendors in 2014 and ended up with 73 in the current 2017 update. Expect this dynamic to continue for the foreseeable future. Even though the BI market is quite mature from the point of view of the number of players and breadth and depth of their functionality, it is still quite immature regarding business and technology maturity, adoption, and penetration levels in user organizations. Vendors will continue to seize this opportunity — new players will keep springing up, and large vendors will continue to acquire them.No market, even a

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Futurology Episode 4: The Future of The Connected Workplace

Michael Facemire

This post was authored by Claudia Tajima, Researcher at Forrester.

 

On the second part of the forth episode of our Futurology webinar series, Mike Facemire, Julie Ask and James McQuivey convened to discuss the future of the connected workplace. Looking forward, they discussed what change in the workplace will look like and what it will take to get there.

See WEBINAR: Forrester Futurology Episode IV: The Future Of Me (Part 2).

 

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