Top 3 customer experience challenges for marketers

Customer experience management is fundamentally about providing a seamless and consistent flow as prospects move through different phases of development and points of contact with a supplier. Delivering on this presumes a level of connectedness that many marketing organizations struggle to achieve. The reason for the struggle is that there are three significant forces of fragmentation opposing their efforts: specialization of roles, organizational hierarchies, and tactical technology. These forces threaten every marketing organization with two fatal flaws: they slow everything down and fracture the customer experience.
Three forces of fragmentation that marketers must fight:
1.     Specialization: all areas of marketing execution have become inch wide mile deep endeavors. As a result, there can be many degrees of separation between key roles such as social marketers, event planners, web administrators, technical writers, etc. What do these people talk about when they get in a room together? Does anyone else care how the events person manages food service or logistics?

How to combat the fragmentation of specialization: It is becoming clear that the one thing all marketing roles now have in common is the need to master data and analytics. Each specialized role produces and consumes data from all the others. It is critical that everyone in marketing understand how customer and operational data flows, how others use the data they produce, and the best analytical practices for gaining insight. This should be a key topic of conversation and community building.
2.     Hierarchical org charts: Marketing is no longer a command and control world. Yes, there is an overlay of reporting that has to go “up the chain.” For many marketing leaders that grew up with the traditional B-school approach to management, adding layers to the org chart is a natural approach. However it results in compartmentalization that left untended creates a culture of disconnectedness.

How to combat the fragmentation of hierarchies: Marketing organizations should be defined around processes not activities. Marketing processes must be supported by collaborative environments that foster greater visibility and coordination between contributors. Enterprise social networks are becoming essential for creating a culture of openness and connection. Organic approaches are not enough, marketing leaders need to seed the social network with process oriented communities such as: campaign management, sales enablement, content lifecycle management, etc.
Transforming Marketing From Silos…
… To Systems
3.    Technology: IDC identifies nearly 90 different categories of marketing technology (not including middleware and infrastructure!) That alone should tell you the function and the IT market serving it are unsustainably fragmented. The deployment of highly specialized tools can empower people within their specialties but can leave them on a technology island in the greater scheme of things. Major IT vendors have started to consolidate some of the basic building blocks, but there are still many areas in which niche/best of breed capabilities are needed.

How to combat the fragmentation of technology: The two centers of gravity for your marketing IT infrastructure are your integrated marketing management solution and your website. They should be intimately tied to each other and all other marketing systems/tools should integrate with one or both of them. This becomes a forcing factor for integrating processes and data flows. Marketers also need to demand more of their technology vendors to accelerate the evolution of platforms that tie together the systems of engagement, content, administration and data.

The most successful CMOs will ensure the pervasive deployment and adoption of technology increases collaboration, socialization, and systems thinking. They will design marketing organizations around customer-centric processes and exert deliberate efforts at all levels to combat the forces that threaten the connectedness needed to serve up a seamless customer experience. 

80% of Your Customer Data Will be Wasted

Larger and richer collections of customer data are increasing available. That’s the good news. But most of that data is wasted. That’s the bad news. Poor data practices remain one of the biggest hurdles to marketing success.

Here are four ways that companies squander data and recommendations about how to stop the waste:

Data is Missing: A huge amount of customer data is available but is just not collected. Your ultimate goal should be to capture interaction and behavioral data at every touch point.
 
What to do: Acquire the data. Invest in marketing technology and services that capture data and in data management technology to store it for analysis. IDC finds that tech marketing leaders invest more than three times the amount of funds in marketing technology than their laggard cousins.  Big data is the marketer’s friend.  Providing lots of data to your analysts will enable them to predict the next best offer, discern buyer preferences, determine marketing program attribution, improve conversion rates, and much more.

Data is Unavailable: Some customer data is captured in company systems, but is trapped where marketing can’t access it. Marketing needs information on customers from a broad array of sources from both inside and outside the enterprise. Sales data, purchasing data, and customer service data, are examples of internally available data critical to seeing the full customer picture.

What to do: Aggregate the data. C-Suite executives must rush to the aid of marketing if they want to get full value from the function. To stop measurement at the MQL or even sales “closed loop” is insufficient for the full customer picture. Pay particular attention to converting unstructured data into structured data so it can help drive the content customization and delivery process.

Data is Junk: Sometimes customer data is captured, but is meaningless.

What to do: Analyze the data. You must be able to separate the signal from the noise. The first step is to gain a baseline understanding of the journeys taken by your best customers.  This point of view will give you a filter. CMOs need to invest in the tools and skills needed to gain insight from the data and tell a relevant business story.

Data is Late: Some meaningful data is captured, aggregated, analyzed – but the whole process takes too long for any relevant action to occur.

What to do: Act on the data. The point of data investment is to develop a rich understanding of the customer’s context so the most relevant response (typically content) can be delivered to them. In a digital dialog, a response is expected on the other side of every click.  Data needs to be made readily available to decision engines and content management systems so that they can take action.

IDC 2014 CMO Predictions

The Chief Marketing Officer cannot avoid broader responsibility as the digital customer experience bursts traditional boundaries. IDC predicts that by 2020, marketing organizations will be radically reshaped. The core fabric of marketing execution will be ripped up and rewoven by data and marketing technology.

What actions will you take in 2014 to gain the most from this future opportunity? Here are the IDC CMO Advisory Service views on the long-term industry trends and new themes that may be on the horizon that will most impact the role of the CMO.
 
To hear more, listen to a replay of our December 17th webinar.
  • Prediction 1 – The CMO role becomes “open for definition” as today’s CMO job description becomes considerably more complex and critical.
  • Prediction 2 – Innovative CMO and CIO pairs will throw out the rule book when it comes to IT’s support of Marketing
  • Prediction 3 – By 2020, the Marketing function in leading companies will be radically reshaped into three organizational “systems” – content, channels, and consumption (data)
  • Prediction 4 – The best marketers will understand that “Content Marketing” does not equal “Thought Leadership”
  • Prediction 5 – Multi-channel coverage becomes an opportunity and a challenge area, as CMOs integrate media silos
  •  Prediction 6 – 80% of customer data will be wasted due to immature enterprise data “value chains”
  •  Prediction 7 – By the end of 2014, 60% of CMOs will have formal recruiting process for people with data skills
  • Prediction 8 – Only 20% of marketers will receive formal training on analytics and customer data management
  • Prediction 9 – Fragmented marketing IT point products and low adoption rate will inhibit companies’ ability to win customers
  • Prediction 10 – Digital marketing investment will exceed 50% of total program budget by 2016

Cross Training for Marketing

Most marketing organizations are organized around a set of silos based on specialized program functions within branding or demand generation. The skills, tools, and relationships needed to manage advertising, events, email, website, social, video production, technical writing, etc. are very different. The pressure and complexity involved in each area can easily turn them into organizational islands. They may each have their own databases, audiences, and reporting structures. They may be further fragmented when replicated across business units and geographies. While specialization is necessary and will only increase, the fragmentation and separation that typically accompany it can break down the customer experience, introduce inefficiencies and redundancies, and slow down the whole marketing operation.
The challenge is how to make strong sustainable connections between specialists so that new competencies can be acquired without the negative side effects. Data management and analytics have emerged as two key skills common to every marketing activity. These topics are ideal for bringing marketers together to share how each of their areas produces and consumes data and the models and tools they use to gain meaningful insights. IDC recommends marketing organizations conduct regular analytics knowledge jams to share competencies, resources, and insights. To cross train them on the many other functions that affect customer creation. Key objectives include:
  • Provide visibility into how data is produced and consumed in other areas
  • Improve data capture, quality, and usability
  • Socialize important analytic models
  • Provide a more holistic perspective on the customer experience
  • Raise the overall data and analytics IQ of the marketing team

In each session, representatives from different groups share 15 minute presentations of what they are working on and how they use data and analytics. This will help combat the fragmentation brought on by specialization, reduce inefficiencies and redundancies, and make marketing more responsive.

Will a Robot Make Your Marketing Job Obsolete?

Cars with no drivers.  Airport ticket counters with only touch-screens. Surgery with no doctors. Automation has taken over human jobs since the industrial revolution. But this trend may be accelerating with the “Great Restructuring“. Which marketing jobs will automation make obsolete?

Time magazine recently published an article titled The Robot Economy which highlights the types of jobs that will flourish (and which won’t) as automation expands. Time says,

“If your job involves learning a set of logical rules or a statistical model that you apply task after task – whether you are grilling a hamburger or issuing a boarding pass or completing a tax return – you are ripe for replacement by a robot.”

Marketing automation is one of the fastest growing sectors of the technology industry, growing at 11.8% in 2012 according to the IDC 2012 Worldwide Marketing Automation Vendor Share Report. Most marketers would agree that marketing automation drives gains for their companies – improved customer engagement, greater marketing accountability, better pipeline management, etc. But is it good for marketing people? The jury is out on whether automation is reducing marketing headcount.  On the precipice of the 2008 downturn, the IDC Tech Marketing Benchmark showed a decline in marketing headcount as a percentage of total employees to approximately 1.5% and the number has sat roughly at that level for the last few years.

Winners and Losers in Marketing Jobs? Nate Silver’s book, The Signal and the Noise, is about making better decisions using analytics. In a chapter about chess, Silver summarizes a 1950 paper by MIT’s Claude Shannon on the benefits of a computer in making decisions versus the benefits of a human.  Claude Shannon said that computers are better at decision-making because:

  • They are very fast at making calculations
  • They won’t make errors, unless the errors are encoded in the program
  • They won’t get lazy and fail to fully analyze a position or all possible moves
  • They won’t play emotionally and become overconfident in an apparent winning position that might be squandered or grow despondent in a difficult one that might be salvage

 Claude Shannon said that humans are better at decision-making because:

  • Our minds are flexible, able to shift gears to solve a problem rather than follow a set of code
  • We have the capacity for imagination
  • We have the ability to reason
  • We have the ability to learn

 Silver concludes that the reason why a computer like IBM’s Deep Blue could beat a chessmaster is that chess is a deterministic game, that is, there is no luck involved. In deterministic situations, where there is perfect information and perfect knowledge of the rules, computers do a better job.  However, wherever there is uncertainty, a better decision will be made if humans help out.

Future proof your career. To ensure you head your career in a confident direction, gain competency in the following types of marketing skills:

  • Solve problems that have never been solved before:  Work that is genuinely non-routine, creative, or paradoxical – such as people or customer management, strategy development, and design.  However, be warned that being creative does not let you off the hook for learning to use data to inform the creative process.
  • Analyze for insight:  While analytic tools will do most of the heavy lifting for us, humans will give meaning to the data patterns as well as to create models, frameworks, and stories for using the analysis.
  • Make unstructured decisions: Unstructured decisions are those where no explicit process for deciding can be put in place – such as an EMT (Emergency Medical Technician). Almost every category of marketing has jobs like this. Put yourself in the line of fire, where there are tough trade-offs, and information is ambiguous. 
  • Persuade: Automation can take over lead nurturing by listening to online data, analyzing it for behavior patterns, and responding with the most relevant selection from a content catalog.  However, blending a human with automation may get you better results.  A leading tech company found that although they can go straight through to purchase using automation, that adding an inside sales person to the conversation increased deal size by 3x.

What ideas have you seen marketers implement to help future proof their departments?

 

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

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. 

3 Steps to Move Closer to the Ever Elusive Marketing ROI

CMO ROIHere at the CMO Advisory Service, we recently closed up our 2013 Barometer Study which includes data from senior level marketers working at some of the largest Tech companies in the world. While there are a lot of great insights from this study, these senior level marketers made it very clear that their highest priority is “Proving Marketing’s Value”, or in other words, that always elusive marketing ROI. While this quest(ion) is nothing new to marketers, as our industry continues its transformation, marketing ROI is becoming an even more pressing topic. We see this truth in our surveys, we hear it from clients, and it is actively being discussed at industry events. This year we launched our  Chief Marketing Officer ROI Matrix (see the image to the right) in an effort to give participants a look into their own return on investment from marketing and continue the conversation. There is no easy answer here (otherwise my days would not be quite as busy), but I have 3 steps senior marketers can take to move closer to measuring marketing ROI.

1. Identify what matters and what does not

This might seem obvious, but to successfully prove value, first it must be understood what is providing value.  Often when we speak with clients we remind them that tactics are important, but without strategy on the front end those tactics may be wasted energy. Before creating a substantial dashboard or reporting tool, take the time to understand which data or measurements are going to further the case and which are white noise. Once done, not only will the organization be better able to prove ROI, but it will be able increase effectiveness.

Key Fact: 27% of B2B companies report they have not yet used predictive analytics to improve any marketing activities.

2. Communicate inside and outside of your department

As transformation continues within the tech industry it is creating a ripple effect to companies and then departments within each company. This means lots of change, and change can often mean confusion. Not only are marketers pushing to prove their worth, but they have to compete with this ongoing confusion. To overcome this issue, communication is a must, both within the marketing organization and across the entire company.  It is key to receive buy-in from stakeholders and make sure the steps taken are continuously aligned with expectations. It also means communicating the actions taken (and why they were taken) to staff or superiors. Remember, over communicate, as in times of turmoil “value” can be a moving target.

Key Fact: In 2013 senior marketers expect 2/3 of the marketing technology budget will come from the marketing department – the rest from IT, Sales, and other areas. Communication across these departments is key. 

3. Benchmark your progress

Identifying what provides value and then communicating as progress is made towards measurment are two great steps. However, when it’s time to share the work, comparisons and baselines will be needed. The first step is measuring your own progress. How have the KPIs improved and what can be expected in the future? The next question will be, what is the comparison to competitors? Finding ways to benchmark and measure progress internally and externally will help tell the story of value added and improvement. It will also set standards and targets to shoot for, without these benchmarks there is a risk of flying blind.

Key Fact: Close to 100 tech companies participated (For Free) in IDC’s Chief Marketing Officer ROI Matrix and benchmarked their marketing ROI against their industry peers. To participate this year contact smelnick (at) IDC (dot) com.

What other steps would you recommend to prove marketing value or even derive that elusive marketing ROI number?

Do you think this is fools gold and there are other areas marketers should be focused on?

Let me know your thoughts!

You can follow Sam Melnick on Twitter: @SamMelnick 

The State of Marketing Operations 2013

Companies simply cannot excel at modern marketing without strong Marketing Operations.  These professionals reinforce high performance by strengthening processes, technology, metrics, and best practices.  A recent study by IDC CMO Advisory Service, in conjunction with MOCCA, found that the Marketing Operations function is flourishing and expanding beyond its original charter.

 

Marketing Operations has been a rising star from its inception. I like to compare Marketing Operations to the structural frame of building. Try to scale without steel girders and you get a weak and wobbly high-rise.  Your marketing will also be weak and wobbly without Marketing Operations.  IDC first recognized Marketing Operations in 2005 in its annual Tech Marketing Benchmarks study.  Then, Marketing Operations represented 2.5% of the total marketing staff. The team became a fast-rising star – driven by the need for marketing accountability and the addition of marketing automation.  In 2012, tech companies averaged 4.4% of their staff in Marketing Operations.  IDC believes that the optimal percentage is between 4% and 6% of total marketing staff. Below 4%, a company will lack the necessary operational capabilities for solid management and transformation. Above 6%, a company should examine whether it’s time to infuse operational capabilities into other functions rather than holding them in a single role.

IDC’s Definition of Marketing Operations:  Internal staff responsible for developing and orchestrating the processes and systems required to enable efficient and effective marketing.  More specifically, marketing operations staff members are responsible for developing and managing the processes to ensure smooth operation of strategic planning, financial management, marketing performance measurement (including dashboard development), marketing infrastructure, marketing and sales alignment, and overall marketing excellence.

In this new study, called Marketing Operations Expands, IDC finds the Marketing Operations function expanding. It has progressed beyond its early charter of planning and resource management to become an important part of lead management and marketing technology among other areas.  More than 70% of survey participants say their role has broadened in the last year and more than 80% say it has become more important. The top six responsibilities for Marketing Automation are: automation, analytics, process improvement, campaign execution, and planning/budgeting. Survey participants, many who are members of MOCCA, the marketing operations professional organization, told IDC that Marketing Operations is also spreading out from its original corporate center to regional teams and beyond its origin in technology companies into new industries.

How should marketing leaders view the expansion of the Marketing Operations role? On the positive side, Marketing Operations can serve as an important and exciting pilot lab for new marketing science initiatives. However, in many organizations, IDC observes that Marketing Operations risks becoming the dumping grounds for not just critical operational tasks, but also for most of the “odd jobs” in the department. Too much expansion, or the wrong kind, results in performance degradation.

For more information on the IDC CMO Advisory Service Marketing Operations Expands research report (which contains important information on organizational structure, skills, job scope, success factors, and much more) check the MOCCA website or contact me at kschaub@idc.com.

Data Analytics wins 2012 US Presidential Election

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.