The Predictive Marketing Analytics for B2B Marketers Forrester Wave

Allison Snow

When my colleague Laura Ramos and I set out to “Wave” the B2B predictive marketing analytics space, we knew that while there are impressive results across the board here, marketers struggle to identify differentiation among its vendors. We’re thrilled to have published Forrester’s first Wave that provides clarification to B2B marketers who seek to connect their business requirements to a predictive marketing analytics solution.

The Wave process begins by screening dozens of interested vendors and each participating vendor – household name or not – brings exceptional capabilities to the market.

We included 11 vendors in the assessment: 6sense, BrightTarget, EverString, Infer, Lattice, Leadspace, Mintigo, MRP, Radius, The Big Willow, and Versium.

Forrester Waves have a track record of delivering objective guidance to technology buyers of all stripes, supported with an interactive tool that marketers can use to zoom in on the capabilities that are important to them. We chose to focus on how well these offerings give marketers the ability to deploy predictive marketing analytics across the customer life cycle, to integrate with other popular martech solutions, and leverage a variety of data sources. Laura and I prioritized the following core principles as we built and assigned weights to each of the 28 criteria:

  • The extent to which solutions can reliably predict an outcome in a specific time frame.
  • The ease with which marketing and sales can execute campaigns using model output.
  • The degree to which model output supports engagement across the customer life cycle.
Read more

Forrester Methodology To Select Business Intelligence Implementation Service Providers

Boris Evelson

Business Intelligence (BI) pros continue to look for outside professional services. Forty-nine percent of decision makers say their firms are already engaging and/or expanding their engagements with outside data and analytic service providers, and another 22% plan to do so in the next 12 months. There are two main reasons for this sustained trend:

  • The breadth and depth of BI deployments cannot be internally replicated at scale. Delivering widely adopted and effective BI solutions is not easy. It requires rigor in methodology, discipline in execution, the right resources, and the application of numerous best practices. No internal enterprise tech organization can claim this wealth of expertise and experience; this only comes after delivering thousands of successful and unsuccessful BI projects — which we believe is solely the realm of management consultants and systems integrators. These partners have collectively accumulated such experience over many years and thousands of clients and projects.
Read more

Is Business Intelligence (BI) Market Finally Maturing? Forrester Three Big BI Market Predictions

Boris Evelson

No. The buy side market is nowhere near maturity and will continue to be a greenfield opportunity to many BI vendors. Our research still shows that homegrown shadow IT BI applications based on spreadsheets and desktop databases dominate the enterprises. And only somewhere between 20% and 50% of enterprise structured data is being curated and available to enterprise BI tools and applications.

The sell side of the market is a different story. Forrester’s three recent research reports are pointing to a highly mature, commoditized and crowded market. That crowded landscape has to change. Forrester is making three predictions which should guide BI vendor and BI buyer strategies in the next three to five years.

Read more

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

Read more

The Data Economy Is Going To Be Huge. Believe Me.

Jennifer Belissent

Are they serious? I've just finished reading the recent Communication on Building a European Data Economy  published by the European Commission. And, it’s a good thing they're seeking advice. The timing is perfect. I’m in the thick of my research for a new report on data commercialization. When I first published It’s Time To Take Your Data To Market the idea was merely a twinkle in people’s eye. Today that twinkle is much

Read more

Divide (BI Governance From Data Governance) And Conquer

Boris Evelson

Stop! Before you invest even 10 minutes of your precious time reading this blog, please make sure it's really business intelligence (BI) governance, and not data governance best practices, that you are looking for. BI governance is a key component of data governance, but they're not the same. Data governance deals with the entire spectrum (creation, transformation, ownership, etc.) of people, processes, policies, and technologies that manage and govern an enterprise's use of its data assets (such as data governance stewardship applications, master data management, metadata management, and data quality).  On the other hand, BI governance only deals with who uses the data, when, and how.

Read more

Business Intelligence Skills

Boris Evelson

So you have gone through the Discover and Plan of your Business Intelligence (BI) strategy and are ready to staff your BI support organization. What skills, experience, expertise and qualifications should you be looking for?

  • Since the term BI is often used to also include data management processes and technologies, let's assume that in your case you are only looking for expertise required to build reports and dashboards and it does not include
    • Data integration (ETL, etc) expertise
    • Data governance (master data management, data quality, etc) expertise
    • Data modelling (relational and multidimensional) expertise
Read more

What To Do When A CIO Pushes Back On Your Agile BI Platform?

Boris Evelson
 
CIO pushback is part of a typical growing pain of all business intelligence (BI) startups. It means your land and expand strategy is working. Once you start expanding beyond a single department CIOs will notice. As a general rule, the earlier the CIO is brought on board, the better. CIOs who feel left out are likely to raise more objections than those who are involved in the early stages. A number of BI vendors that started out with a strategy of purposely avoiding the CIO found over time that they had to change their strategies - ultimately, there’s no way round the CIO. Forrester has also noticed that the more a vendor gets the reputation of “going round” the CIO, the greater the resistance is from CIOs once they do get involved. 
 
There is of course also the situation where the business side doesn’t want the CIO involved, sometimes for very good reason. That notwithstanding, if there’s a dependency on the CIO when it comes to sign-off, Forrester would strongly recommend encouraging the business to bring him/her to the table. 
 
The two key aspects to bear in mind in this context are:
 
  • CIOs look for transparency. Have architecture diagrams to hand out, be prepared to explain your solution in as much technical detail as required, and have answers ready regarding the enterprise IT capabilities listed below.  
Read more

It's 10 O'Clock! Do You Know If Your BI Supports Actual Verifiable Facts?

Boris Evelson

Delivering broad access to data and analytics to a diverse base of users is an intimidating task, yet it is an essential foundation to becoming an insights-driven organization. To win and keep customers in an increasingly competitive world, firms need to take advantage of the huge swaths of data available and put it into the hands of more users. To do this, business intelligence (BI) pros must evolve disjointed and convoluted data and analytics practices into well-orchestrated systems of insight that deliver actionable information. But implementing digital insights is just the first step with these systems — and few hit the bull's eye the first time. Continuously learning from previous insights and their results makes future efforts more efficient and effective. This is a key capability for the next-generation BI, what Forrester calls systems of insight.

"It's 10 o'clock! Do you know if your insights support actual verifiable facts?" This is a real challenge, as measuring report and dashboard effectiveness today involves mostly discipline and processes, not technology. For example, if a data mining analysis predicted a certain number of fraudulent transactions, do you have the discipline and processes to go back and verify whether the prediction came true? Or if a metrics dashboard was flashing red, telling you that inventory levels were too low for the current business environment, and the signal caused you to order more widgets, do you verify if this was a good or a bad decision? Did you make or lose money on the extra inventory you ordered? Organizations are still struggling with this ultimate measure of BI effectiveness. Only 8% of Forrester clients report robust capabilities for such continuous improvement, and 39% report just a few basic capabilities.

Read more

Insight Platforms Have Arrived

Brian  Hopkins

Are you lost in a confusing soup of vendor-speak about what their data analytics stack actually offers? Big data, data platforms, advanced analytics, data lakes, real-time everything, streaming, the IoT, customer analytics, digital intelligence, real-time interaction, customer decision hubs, new-stuff-as-a-service, the list goes on.

Recognize the convergence happening as vendors evolve their technologies from doing just one thing like predictive analytics or search to many things together. For example, data integration, data warehouse, and BI tools are typically sold separately, but breakout vendor Looker combines data integration, model governance, basic BI, and a runtime for data applications all in one software layer that sits on your data lake. As another example, consider predictive analytics vendor Alpine Data Labs or SAS Viya from SAS. These vendors have built out a lot of data management and insight delivery tooling into their platforms because without it users struggle to maximize value. Another trend is big data search vendors like Maana that now also include hooks for predictive model execution as well as more data management functions. Lastly, systems integrators are packaging their IP and offering it as a data management and analytics integrated product — for example, Saama’s Fluid Analytics Engine or Infosys’ Information Platform.

In fact, the list of innovative vendors blending data management, analytics, and insight execution technology is growing by leaps and bounds. To address this trend, I just published a report, Insight Platforms Accelerate Digital Transformation, in which I created a broad definition that labels this trend:

Read more