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Showing posts with label Big Data. Show all posts
Showing posts with label Big Data. Show all posts

Monday, 22 July 2013

If Content is Still King, Data is Heir to the Throne

Posted on 06:00 by Unknown
Content marketing is becoming a primary strategy to solve the challenges of massively scaling and diversifying marketing channels. But content does not naturally support both scale and diversity at the same time. The only thing that scales as endlessly and cost effectively as the digital world is data. As a result, data marketing is on the rise and will ultimately inherent the throne as the core strategy for modern marketing. What is data marketing? It's using interactive data to directly influence or add value to your prospects, customers, and partners. Think of it as content marketing without the editorial. Data marketing is already fueling the rapid growth of content marketing. The best pieces of content marketing are typically wrapped around a compelling piece of (static) data. The key is that stripped of editorial, data must become interactive and not only deliver personalized insights but capture and bring user input back. 

Modern business solutions are increasingly deployed in the cloud on SaaS platforms that capture every transaction of every user. SaaS vendors are finding huge value in these datasets. They provide empirical evidence of best practice, efficacy, and cost effectiveness. Marketing and sales automation vendors can show their customers and prospects what types of campaigns result in the greatest lead generation, the highest value and velocity through the pipeline and the greatest return. They can tell them what type of social media content and cadence is most effective on which social media channels. This insight represents enormous value-add over and above the operational efficiency the systems provide.

Consider the power of this model applied to channel marketing. A SaaS platform for channel enablement can offer partners a single point of access to content repositories, transaction systems, execution environments, (inbound and outbound marketing, sales process tools) and social networks. If it's constructed properly it provides a place for partners to get work done, not just a library to read about how to get stuff done. For smaller partners that lack infrastructure and staffing resources this is an invaluable resource. As they use the platform it captures:
  • Engagement – who's downloading what how often from the platform
  • Transactions – deal registration, order submission, billing update, MDF reconciliation.
  • Execution– the number of leads their marketing has produced, how leads are progressing through their pipeline
  • Social interactions - groups they join, how they participate, what SMEs they interact with.
  • Performance data – closed deals, order value

Access to this data can be offered from the platform through the development of a few simple forms and reports. The more data partners provide, the greater the level of analysis and insight they get in return. This information can be used to identify best practices of the top performers and shared (in aggregate) with other partners to help them run their businesses, resulting in better overall performance of all partners.

By utilizing pure data as collateral, companies can deliver highly targeted proprietary insights at scale much more efficiently than they can with content. While the role of content will in no way diminish, companies that master the art of data marketing will have greater levels of engagement, retention, and revenue with all their key constituents than those that rely exclusively on content marketing. 
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Posted in analytics, B2B Marketing, Big Data, channel marketing, content, data, Digital Marketing, Gerry Murray, marketing as a service, Marketing Automation, Measurement, partner marketing | No comments

Thursday, 27 June 2013

Using Data as a Service for Scalable Channel Enablement

Posted on 13:48 by Unknown
The magic ingredient for successful channel enablement at scale is data. Imagine having the financial, operational, and behavioral data you need on partners to optimize new product launches, coverage models, and channel programs. Imagine being able to show partners — no matter how new or small or niche their focus — how other partners like them have achieved high return on investment (ROI) on their business with you. IDC's Channel Enablement Maturity Model provides a stage-by-stage guide for advancing the organizational, process, technology, and data infrastructure necessary to transform your channel marketing and sales enablement operations. The journey along IDC's Channel Enablement Maturity Model is one of evolving from a publishing/transactional framework to a process-driven one.

IDC's Channel Enablement Maturity Model - Summary View

Stage 1:
Ad Hoc
Stage 2: Opportunistic
Stage 3: Repeatable
Stage 4: Managed
Stage 5:
Optimized for Scale
Key characteristic
"Every product for itself"
"Portals grow like weeds"
"Consolidation but still stuck in publishing mode"
"Central control over process-driven approach"
"It's all about analytics (Data as a Service)"

Source: IDC 2013

The DNA for Success is in the Data 
IDC defines channel enablement as "developing the right competencies in the right partners to deliver the right solutions to the most profitable customers." Ultimately, the goal is to provide a scalable model to identify high ROI best practices and propagate them throughout the partner population at a very granular level. There are three ways in which manufacturers can capture the partner data needed to support the analysis:

  • Contractual obligation: Requires significant time and effort from partner account management, is limited to the largest partners, and is periodic at best. 
  • Operationalized data capture: The partner platform should be thought of as a SaaS offering that provides a wide range of functionality but also collects data on every partner interaction. The ideal platform will consolidate all of the interactions with partners by offering personalized access to content and transactional systems, as well as execution platforms for marketing, sales, and support. By virtue of this consolidation, it captures an increasingly large portion of partner interactions and thus provides a great deal of valuable data to inform channel marketing and management. 
  • Data as a service: Externalize partner performance data and make it available to partners in a way that captures even more data from more partners. The level of detail they get depends on the level of detail they provide. As a result, they can get actionable insights on how to better manage their businesses and market, sell, and support specific solutions. The database is in a virtuous cycle of enrichment. They should be able to get insight into a wide variety of strategic and tactical questions such as: 
    • How many people do I need in marketing, sales, technical, and support roles? 
    • What level of skills and training should they have? 
    • What marketing activities are most effective? 
    • What sales methodologies and plays are most effective at what stage? 
    • What manufacturer resources and networks should staff be utilizing most frequently? 

While data is the crown jewel, there are significant people, process, and technology prerequisites for success. To find out more please see IDC's Channel Enablement Maturity Model or contact me at gmurray (at) idc (dot) com.
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Posted in B2B Marketing, Best Practices, Big Data, channel marketing, Gerry Murray, Sales Enablement | No comments

Thursday, 8 November 2012

Data Analytics wins 2012 US Presidential Election

Posted on 08:13 by Unknown
Data analytics was the big winner in the 2012 US Presidential race. In fact, 11:17 PM (US ET) November 6th was the moment data analytics went mainstream. This was when Ohio was officially projected to go to Obama. It was the ultimate validation for Nate Silver and his data analytics approach to election forecasting. To much fanfare he accurately predicted the results of the election in all 50 states without doing any of his own polling. He used sophisticated analytic models based on data from as many third party polls he could find. To this he added the secret sauce of data analytics - a keen understanding of how different types of data from different sources relate to one another in context.

His FiveThirtyEight blog drove as much as 20% of the web traffic to the New York Times website - the 6th most visited US news site on the net - leading up to the election. As a result, data analytics is officially mainstream. Any business leader at any level that does not immediately embrace its power is putting his or her career and company in jeopardy.

Data analytics works. It does not produce miracles, but it does produce results that far outperform human judgment on its own. The Obama campaign employed an army of retail data analytics wonks to beat the Romney campaign in every battleground state. They did it by applying analytic techniques proven in the supermarket industry:
  • Standardizing records: Unifying the customer (voter) database
  • Widening perspective: Combining diverse data types: demographics; buying/voting history; response by media; donation/activity by trigger (celebrity dinner), model (contest) and method (mobile); group/church  membership, social networking activity (Reddit), etc.
  • Judicious targeting: Carefully identifying the potential for influencing voters that could influence the election. Not worth targeting easily influenced voters if they don't live in a county that can help swing a state. Not worth targeting difficult to influence voters even if they live in a critical county. This is essential for achieving impact and ROI.
  • Media mix modeling: which media channels have the greatest impact on which kinds of voters?
  • Action oriented outreach: Understanding the specifics of why and how certain people act and designing multiple outreach experiments (progressive offers, channel mix, social references, etc.) based on that.
  • Openness to innovation: data driven models may point to approaches that are counter intuitive for some decision makers. They can seem risky and mysterious. They will not be right all the time. Controlled risk is part of the evolutionary process to effectiveness. Without a tolerance for experimentation however, you will not develop a data driven culture, you will in fact kill it.

Marketers in the world's largest high tech companies are finally acquiring the enterprise data services needed to apply data analytics to long cycle B2B customer creation processes. We are already seeing signs of how significant the impact of these new approaches to marketing and sales can be:

  • $200M EU lift based on a sophisticated solutions recommendation engine
  • 45% more subscription revenue with no increase in a multi-million dollar marketing budget
  • Tens of millions of dollars in revenue uplift from simple web behavioral changes

Embracing data driven decision making is now a matter of survival. You simply cannot win against competitors that have faster, deeper market insight. They will beat you in every stage of the customer creation process. Your marketing will be months behind, your inside sales reps will be calling customers already committed to alternatives, your field sales reps will miss opportunity after opportunity to get more revenue from existing customers. Your funnel will collapse, your pipeline will dry up, your renewable revenue will shrink, and at that point it will be hard to recover. Hyperbole, you say? In the great A/B test of who uses data analytics and who does not, stay in the B group at your peril.

IDC EAG group has done extensive research on the key ingredients needed to create the enterprise data services that are a prerequisite for data driven customer creation and has ongoing research into how to create a data driven culture. To find out more please contact Gerry Murray - gmurray(at)idc(dot)com. 
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Posted in analytics, Best Practices, Big Data, Campaign Management, CMO Guidance, customer creation, Digital Marketing | No comments

Friday, 11 May 2012

Big Data Comes to Marketing?

Posted on 06:41 by Unknown


What's the most commonly heard word in marketing organizations today? It is “Transformation.”

Dramatic transformational change is sweeping through marketing functions in most industries. And the main "change agent" is the customer. Or what we at the IDC Executive Advisory like to call the "New Buyer" . Our customers and prospects today are crafting their own routes to learning about products and services. They are motivated and skilled at educating themselves and learning from peers. They travel through numerous digital pathways in their exploration process. And by the time they come to a meeting with the vendor sales person, they are smart and savvy. They are empowered.

Marketers need to ask and answer these questions: Where did our Buyers come from? What do they know already? And above all: How do we  add new value to where they are in the process of discovery about our product or service? The New Buyer dynamic creates volumes of new data and customer intelligence analysis opportunities for vendors.

In turn, Those in the marketing job function must be able to bring better data into any planning meeting, including discussions on budgets and investments; programs and campaigns; or performance measurement. Hard data needs to complement the “softer side,” or the “art,” of marketing.

The tools for accessing and mining data, and turning data into insights, are now plentiful for today’s marketers. And, The marketing job function might be the last of all an organization’s major functions to become automated.

The marketing winners of tomorrow will be masters of rapid data management — able to turn data into intelligence, intelligence into analysis, and analysis into decision support and execution. Achieving this will be the first step in the rudiments of sales-to-marketing cost control.

For the CMO, there are three critical, inter-departmental, data-driven intersections that need to be created and nurtured. Marketing is now too important to run in isolation, so here are the three key intersections:

1. The Marketing and CIO intersection. New IDC research shows that the investment in marketing automation technologies in 2012 will be at three to four times the rate of 2011 levels. Automation technology development is going to sweep through sales and marketing over the next 10 years.

2. The Marketing and Sales (CSO, or Chief Sales Officer)  intersection. Today, the CMO needs to be able to connect sales technologies, such as CRM, with new marketing automation technologies.

3. The Marketing and CFO intersection. The CMO needs to deliver a return on investment in measurable terms in order to have meaningful budgeting and planning discussions with the CFO. Measuring impact of push programs in terms of conversion to leads, opportunities, and revenue is the game today.

I like to say that there will be more change in Marketing in the next five years, than we have seen in the past 25 years combined. These Marketing data and IT automation issues will be at the forefront for the next generation of successful CMOs.
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Posted in B2B Marketing, Big Data, CMO Guidance, CRM, IDC, Marketing Automation, Marketing Operations | No comments
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