Uncertainty: The hidden barrier in B2B markets
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Many B2B purchases are delayed or abandoned due to the uncertain outcome of the decision. Prospects compare the certainty of the status quo (good or bad) to the potential (but uncertain) benefits of a new solution and opt for the “devil they know”. The implication: B2B Marketing and Sales can help prospects reach a purchase decision by reducing uncertainty for the new solution, and increasing uncertainty of the status quo.
A recent study by Jeffrey Pfeffer, a professor at the Stanford Graduate School of Business shows that individuals favor certainty of outcome over potential benefits – they choose a certain loss of $100 over a chance to flip a coin with the chance to pay $0 or $200. Complexity exacerbates the problem. With more moving parts in the equation, people find it increasingly difficult to envision how the future will play out.
It turns out it’s not Go with the devil you know. It’s Go with the devil you know over anything else – unless you are absolutely sure about the other option.
Companies and B2B markets tend to follow the same pattern: The more conservative the company or market, the more dramatic the effect. The preference for the known plays itself out daily across markets and organizations.
- As prospects go through their evaluation process they ask for more information, details, case studies, etc. in an effort to bring certainty in their decision. In a recent post Make it easy for prospects to buy we explored how providing all the information prospects request doesn’t help get prospects over the hump and to the buy decision – it bogs them down further.
- Flip through a B2B trade publication and you’ll see that many of the ads look the same and don’t change much over time. Behind the scenes, B2B marketers ask their creative agencies to help their brand stand out in the marketplace. However, most B2B brands stick with the original creative strategy because its performance is more certain.
- Research reports that present the data as %’s often get more attention than qualitative insights because a number feels more certain than a description – whether it is or not.
- It took almost a decade for most markets to become comfortable with cloud software solutions. They knew the cloud offered significant benefits over their on-premise solutions, but most companies didn’t want to move until they saw that the cloud was here to stay and that everyone else was doing it too.
Pain points trump benefits
Perhaps the most basic, yet important, manifestation of this trend is that solving pain-points represents a more effective sales and marketing strategy than selling benefits. Here’s why…
- Pains are certain. Concrete. They are something specific the prospect knows it needs to address. Once a pain gets significant enough the desire to find a solution outweighs the uncertainties that come with new approaches and vendors.
- Benefits are hypothetical. If a prospect does x, y, and z, they should receive the benefits. Benefits raise questions: What if a key assumption turns out to be false. Benefits come with more professional risks. Unrealized benefits lack the certainty of the status quo.
The insights from Pfeffer’s research and the day-to-day experience of B2B sales and marketers leads to one conclusion: B2B sales reps and marketers need to change the uncertainty equation.
- Increase the certainty of new solutions
- Decrease the certainty of the status quo
Increase the certainty of new solutions
Recognize and acknowledge the uncertainty
Left to their own devices individuals and businesses can easily overestimate the things that can go wrong with a new approach or soluiton. By acknowledging the risks that exist, vendors can set the parameters of what the risks and uncertainties actually are. This can include letting prospects know where other individuals/companies run into trouble, what needs to be in place for the solution to be a success, etc. Acknowledging uncertainty not only frames the issue, it increases the knowns associated with the new solution.
Create specific certainties
Reducing the number of unknowns (even minor ones) makes options look more appealing. This phenomenon is known as zero risk bias which is the tendency to prefer options that completely eliminates some risk factors in a decision but leaves other untouched, over options that may produce a greater overall reduction in risk, but do not eliminate any individual risk factor. The preference for options that completely eliminate some risks likely stems from the reduction in complexity – it reduces the factors that have to be considered in the decision.
Examples of certainties that B2B vendors can create include:
- Concrete implementation processes and milestones
- Metrics of how other customers use the solution, e.g. 75% of customers select this approach
- Definitive outcomes, e.g. the ads will stand out from competitors (which is different than saying they will be effective)
- Customer satisfaction scores
- Guarantees / Shared risk models
Raise the uncertainty of the status quo
While the status quo feels stable to individuals and organizations, it’s not. Sales and B2B marketers can point out this false sense of security by asking questions or providing data that highlight the actual uncertainty associated with prospects sticking with the status quo: Your market appears to be changing in this way, how will that effect you? These new entrants have entered the marketplace, what does it mean for your market? etc. etc.
There is no single approach or silver bullet for changing the certainty equation. Prospect perceptions of, and preference for security are rooted deep. We suggest a few starting points:
- Examine the customer journey to ensure you understand their status quo and pain points.
- Identify the benefits of your solution that are most believable to the market, and therefore have greater certainty.
- Analyze the Marketing and Sales Process. To what extent does your approach (advertising, collateral, sales process, etc.) reduce or increase certainty for the buyer?
These steps will help sales reps and B2B marketers look more certain in an uncertain world.
Do some prospects slip away at the last stages of their buying journey, even though it seems your sales and marketing teams have done everything right? You may inadvertently be making it difficult for some prospects to make a decision. The following illustrates how this situation arises, and how to avoid it (names have been masked to protect the guilty).
Yellow Manufacturing seemed ready to buy Acme Tech’s CRM solution. It had conducted research about the solutions available prior to reaching out to vendors set a preliminary budget, etc. prior to reaching out to vendors. Acme provided extensive information about its CRM suite, outlined the different options available, demonstrated everything the solution could do and answered every question Yellow raised. But after months of back-and-forth Yellow put the initiative on hold.
What happened? Acme made it difficult for Yellow to make a final decision by providing too much information. In short, Yellow wasn’t ready to process the amount of information Acme provided and ended up with analysis-paralysis.
The tendency to overestimate readiness to buy stems from a misinterpretation of the new buyer journey. Many articles from the past few years talk about how prospects are 70% (or some comparably high %) or more through their buying journey before they reach out to vendors. These data suggest that when the prospect calls a vendor, they have objectively worked through their needs, know what they want and are at the stage of collecting the specific information necessary for vendor selection.
In reality, for many prospects the first 70% of the purchase journey focuses on the rudimentary elements of the buying decision. Yellow identified the problem that needed to be solved, the type of solution that might be able to help them, and some vendors that provide that type of solution. Their knowledge was still broad and thin when they reached out to Acme and competitors. Yellow may have been through 70% of their journey, but as with many situations in business and in life, it’s the last mile where the real learning, thinking and challenges take place.
When Yellow reached out to Acme CRM, it still needed to determine whether to invest in a solution at all. By providing stacks of information about its products, Acme increased the dimensions Yellow needed to consider, raised questions Yellow hadn’t thought of before, and made the solution and decision feel too big. Collectively this slowed down the decision process and eventually knocked Yellow out of the sales funnel.
This confusion about Yellow’s readiness to purchase isn’t entirely Acme’s fault. Prospects like Yellow can contribute to the impression that they are an informed buyer. Consciously or note, Yellow worried about being taken advantage of by Acme’s sales team and process, and presented themselves as knowing more than they did. Yellow knew the buzzwords, and had specific questions—they talked a good game. In addition, when faced with complex questions, people often substitute a smaller, easier to understand questions in place of the hard ones. Many B2B technology solutions raise big picture considerations about business processes, integration, how ROI will be measured, etc. The list of specific questions Yellow asked Acme CRM reflected a need to get their head around the solution, rather than an indication that they just needed a few more details to finalize their selection of vendor.
Improving the last mile.
Vendors can implement two related strategies to improve their effectiveness and win-rates during the last phases of the prospect buying process.
- Map the last 30% of the buying journey in more detail
- Use a prescriptive sales approach
Mapping the last 30% of the buying journey
When B2B marketers map the buying journey, many tend to focus on the steps in building awareness and consideration, which happens to be where marketing has the most responsibility. However, by paying as much attention to mapping what happens after a prospect engages with the sales team can enable their company to close more deals. Some of the key aspects to explore include:
- How knowledgeable and informed is the typical prospect when they begin to interact with the sales team. This helps marketers and the sales team set a baseline for creating materials and processes that speak to prospects in a way, and at a level, they can understand.
- Identify the 2-3 core drivers of the buyers purchase motivation—even when buying the most complex product, most prospects are focused on improving a handful of key activities. This will provide a framework for marketers and sales team to speak to the benefits that prospects care most about – instead of a range of things that are interesting but unlikely to influence their purchase decision.
- Determine the internal barriers your internal champion is likely to encounter and provide data and recommendations for how they can overcome them. Once your champion is sold, the deal can still be derailed if they cannot sell it internally.
Use a prescriptive selling approach
When prospects reach out to vendors most are still trying to understand what solutions would be the best fit for them and whether to should invest at all. Many ask for different options because they don’t really know what they need and hope that one of the options presented will stand out as the right choice for them. Instead too many options can confuse the issue. Research conducted by CEB shows that vendors that take a prescriptive approach—provide a recommendation with a clear rationale instead a series of options—close significantly more deals.
That said, it is important for your recommendation to be in line with the core drivers of the prospects purchase motivation. Prospects tend to reject solutions they view as too broad in scope relative to what started them down their purchase journey. Put another way, presenting your entire suite of products can knock you out of the running if the prospect is focused on a single module.
Making it easy for prospects to buy
The vendor that makes it easy for Yellow to make a decision by presenting information they can understand, addressing Yellow’s core needs, and presenting a recommendation instead of options, is most likely to win Yellow’s business.
While B2B marketers wait for their organizations to adopt big data tools, they can leverage a range of cost-effective data sources to inform decisions that move their companies forward.
The following are some of low-cost or free data sources (little data) B2B marketers, product managers and strategists can use to evaluate market opportunities, competitors, customer needs and overall market trends.
- US Census
- Publicly available reports/articles
- Mining internal data
- Interviewing sales reps and account managers
- Deeper read of customer survey data
- Social media and job sites
- Conducting win/loss interviews
- Reference class comparisons
Hoovers/D&B (or other list sources)
Hoovers (www.hoovers.com) self-service, prospect, list-building tools can help determine the number of businesses in a segment. Once you set your parameters (e.g. Hospitals with at least 500 employees) Hoovers provides counts for the number of businesses in that segment overall and in sub-segments (e.g. hospitals with 500-1000 employees). You can refine your search, start over, etc. to get more data. You don’t pay unless you purchase a list.
US Census Bureau
The Census provides similar data to Hoovers, but has the advantage of historical data which allows you to see if a segment is growing/shrinking (www.census.gov/econ/). One downside is that the Census’ search tools are clunky.
Publicly available reports/articles (desk research)
B2B marketers need to understand the segments they serve, or plan to enter. Insights into market trends, product use, and market dynamics can be gleaned by reviewing publicly-available reports and articles. Government agencies and trade associations produce reports on broad economic trends and share data from market surveys they conduct. Each industry also has its own trade publications that discusses overall trends and challenges.
Analyst reports profile specific markets and product categories. Most analyst reports charge for full access, but there are often nuggets of information in the free synopsis. In addition, the data source is often cited in other publicly-available sources such articles and vendor marketing materials (e.g. we are in the Magic Quadrant).
Many B2B companies issue press releases when they acquire a new customer, make an acquisition, form a partnership, etc. providing insights into the direction the competitor is headed.
Having a reference librarian or researcher can make the information gathering from these sources much more effective and efficient – simply Google searches can waste a lot of time on a goose chase.
Mining internal data
Sometimes, B2B marketers don’t know what data they available because it is spread out across the organization in different systems and databases. Conducting an information audit will identify the data available for analysis. Taking it a step further, combining the disparate data into one database or spreadsheet can provide surprising insights through simple cross-tabs or pivot tables. If you have more advanced analysis/reporting tools, all the better. Some companies have staff and tools that make pulling the data together easy. In others, B2B marketers must slog through the merging, cutting and pasting data and data files.
Interviewing sales & account reps
Sales and account reps have more direct contact with customers and prospects than anyone else in your company. You can use informal one-on-one conversations, structured round-table discussions or simple online survey tools to explore the requests they receive from customers, competitors they see in the market, solutions in place, etc. Their feedback may be biased towards short-term sales, but it can still provide insights into overall market trends.
Deeper read of customer survey data
VOC and NPS surveys provide a great deal of data beyond the overall score – which often gets the attention. For example, reading through the full set of open-ended comments provides context and texture around customer needs. Combining other customer data with NPS data allows you to look at trends and differences across different type of customers (e.g. product segment, sales volume, tenure as a customer, etc.). Manually creating a spreadsheet that combines the data is cumbersome, but often faster than trying to get things combined in your ERP or CRM system.
Social media, and job sites
LinkedIn, Salesforce’s data.com, and Hoovers provide insights into a competitor’s number of employees and revenue. You can see how many staff are devoted to sales and marketing activities, where sales reps are located, etc. Each source will have a slightly different number for these metrics but by looking at more than one you will triangulate on a usable estimate.
Jobs sites such as Indeed.com and the Hiring section of a competitor’s website can indicate if the company is growing and their focus (e.g. are they hiring more marketing people than would be expected, a certain type of engineer, etc.).
A search of SlideShare can uncover sales and investor presentations and similar materials that show how a competitor is presenting itself to the market.
Conducting win/loss interviews
Conducting interviews with recent wins and losses provides insights into the market’s decision process, vendor evaluation criteria, and how you compare to competitors. Win/loss interviews are best conducted by a third-party partner. If using an external partner isn’t in the budget, the interviews should be conducted by someone not connected to the sales process.
Reference class comparisons
The goals of data-driven decisions are to predict the future and narrow uncertainty. Reference class comparisons—an analytical approach, rather than a data source—can help frame likely future outcomes. The past doesn’t necessarily predict the future, but it’s a good place to start. Future product introductions, acquisitions, entries into new markets, etc. are likely to unfold similar to previous efforts. If you predict that the new effort will be significantly different from the past it forces you to evaluate and identify the data that supports your assumptions.
Tying it together
The secret sauce of big data is that it combines disparate data to form a conclusion based on the relationships that exist. Big data uses algorithms, models, and machine learning to create an outcome that is greater than the sum of its parts. B2B marketers do this daily using little data, basic tools and their experience and judgement – the original big data machine.
Collecting and combining the data sources is time consuming and tedious. It also doesn’t answer all the questions – every decision is based on incomplete data. However, it’s worth the effort: It provides insights that will help B2B marketers evaluate market opportunities, competitors, customer needs and overall market trends.
Expected product life cycles have traditionally informed forecasts for software demand – they could be used to help estimate the number of organizations likely to be in play any given year because their solutions had reached their natural refresh cycle. The shift to cloud applications muddies the water in terms of this traditional forecasting approach.
Cloud solutions lack a natural life cycle – the technology doesn’t wear out. Unlike legacy on premise software cloud solutions aren’t tied directly to the organization’s infrastructure or the software’s old code. As a result:
- There are fewer natural refresh cycles where organizations look to update their data center and enterprise applications at the same time.
- There are fewer sunk costs where organizations need to use their solutions for a set number of years to achieve the required ROI.
- Contracts, where they exist, have shortened freeing organizations to switch vendors without penalty.
However, these changes do not mean that cloud applications don’t have a life cycle of sorts. They do, but they are driven more by human interactions and expectations than on technology.
Based on our research in various markets we believe the average cloud solution will have a 4-5 year human life cycle and will unfold as follows:
Year 1: Transition
Despite the ease and speed in which cloud solutions can be deployed, deployment does not equal immediate productivity. It takes time for people to learn new systems and processes (regardless of how easy they are to use). And the longer an organization has been using its previous processes the longer the conversion process – it takes a long time to teach old dogs new tricks. In the end it generally takes a year for people to become comfortable with a new system and achieve the productivity and efficiency it is designed to provide.
Years 2-3: Maximum benefit
Once the solution becomes the new norm, employees and the organization will receive the maximum benefit of their investment. The solution will be delivering the core set of benefits the organization hoped to achieve. These are likely to be tactical areas of improvement.
Years 4-5: Diminishing returns
After four years or so a number of dynamics are likely to unfold.
- Organizations will begin to have more complaints about their systems and find that they cannot do everything that they would like to do. This may be due to the solution’s failure to delivery on the strategic functionality promised, or simply an increase in the organization’s needs and expectations.
- New vendors and technologies will have entered the market with buzz and hype: The grass is always greener and older solutions tend to get pigeon-holed into what they were originally purchased for, even if they can provide the new functionality.
- Over the course of 4-5 years there will be some inevitable staff turn-over and new decision-makers will enter the organization. New decision makers often bring solutions they had success with in prior organizations into their new ones.
All of these contribute will contribute to a general tendency for organizations to begin to consider other vendors and conduct their due diligence – like they always have.
So what does this mean for vendors in terms hoping to win market share from competitor cloud solutions? On the up side, markets are likely to look at new systems on a more frequent basis. Unfortunately, like on premise solutions before them, cloud applications inherently have a barrier to switching – inertia.
One reason organizations stick with the solutions they have—even when they believe better solutions exist—is that the solution they have works well enough and the benefits they gain by switching don’t outweigh the pain and suffering that comes with switching. Cloud solutions reinforce this trend because they constantly update making it more likely that they remain good enough to stick with. This is an advantage once you have customers using your cloud solutions. But, it means to motivate prospects to switch vendors will have to provide concrete and significant benefits over existing cloud solutions. This may be enhanced functionality, integration with other systems, specialization, customization, a higher level of customer support, etc. But it cannot just be an easier to use system or a reliance on dissatisfaction with another cloud system – they will never be that old or that hard to use.
Cloud applications prove the proverb; the more things change the more they stay the same. There are forces at work creating both inertia and switching motivation. The shift in life cycles is that traditional models are based on the product itself, the new is based more on how the solutions are used by humans.
A recent article on forecasting presents historical data and judgment as an either-or choice. We disagree. In our view, the art of forecasting requires both and the understanding of how much weight to place on each depending on the circumstances.
The article outlined research conducted by Dr. Matthias Seifert and his team at The IE Business School in Spain. They evaluated the value of historical data vs. judgement in forecasts for volatile sectors such as fashion and entertainment. These fast moving markets provide a compressed, microcosm to study how demand unfolds at a slower pace in other markets – similar to how geneticists study fruit-flies to understand the transmission of genes in humans. Their data indicate that in volatile markets, historical data provide limited value for predicting the success of new products. For example, forecasts based on a musical artist’s last album do a poor job of predicting the success of their next endeavor. The forecasts become more accurate when based on predictor variables such as the amount of marketing behind the first single and the other artists releasing music at the same time.
This may seem obvious, but that is due to the simplicity of the example. The dynamic exists in more complex markets and situations, it’s just harder to see. The business literature is strewn with examples of companies that based their forecasts and strategies on the status quo rather than look at variables that predicted a change in demand and paid the price (Kodak, Blackberry and Microsoft to name a few). The obvious ones to consider include the current competitive set, existing products, and marketing activity. Innovators and disruptors such as Steve Jobs and Elon Musk take the process a step further and evaluate factors such as products and competitors that may enter the market and what people are trying to accomplish rather than the specific products they use. Seeing the broader picture comes naturally for people like Jobs and Musk. For the rest of us, the book Winning the Long Game: How Strategic Leaders Shape the Future by Steve Krupp and Paul J. H. Schoemaker offers some pointers and practices for looking beyond the status quo.
One of the primary challenges with identifying predictor variables is that they aren’t always evident. As a researcher Dr. Seifert had the luxury of comparing past actions and circumstances with outcomes. The second challenge is that it is easy to get carried away in identifying tenuous predictor variables and then assigning them more power than they likely have in order to create a plausible scenario that fits the outcome we are seeking. Using a reference-class comparisons and historical data provide a disciplined way to reign in this tendency. It involves systematically evaluating historical trends and what other organizations have experienced and asking the question: Why do we expect things to be different. This exercise helps put your hypotheses and variables in perspective and clarifies the degree to which they are likely to make the future different than the past.
At Isurus we include predictor variables and historical data when designing forecasting surveys. Predictor variables include brand awareness, information sources, price, etc. Pain points, desires and motivations fall into this category as well. It’s cliché, but people don’t want to buy a drill – they want a hole. Historical data and reference class comparisons aren’t perfect predictors of the future – but in most cases they are within a standard deviation or two from it: If consumers or businesses have always purchased on price, they are likely to continue to do so in the future.
We think the big take away is that the best forecasts use both historical data and judgement. To ensure you systematically include both, use these three questions when creating your next forecast:
- What would history predict the future would be?
- What factors got the market to its current state? (Level of marketing, competitors, technology, features and functionality, etc.)
- What might be changing or might we proactively change that would make the future different from the past? (New delivery model, combination of features, etc.)
Customer centricity is reshaping IT in many organizations, as customer experience becomes an increasingly important source of competitive advantage. We’ve seen this trend developing over the past few years and it is now gaining widespread attention. Customer centricity means aligning IT’s resources and objectives to optimize the customer experience. Increasingly, IT’s strategies, organizational structure, and role in the organization are evaluated in relation to the external customer.
The shift to customer centric IT impacts:
- Goals and objectives: IT’s overall goals become more aligned with customer and business objectives. Rather than viewing internal business functions as its customer, IT works to build its knowledge of the external customer. This is a significant change in mindset for most IT functions, with wide ranging impacts on organizational structure within IT, relationships with the business functions, and staffing at all levels within IT.
- Organizational structure: IT becomes less isolated and more integrated with the business and customer-facing operations. IT organizations are creating new roles and teams—like Business Relationship Managers and Customer Engagement teams—to act as a bridge between business functions and IT’s technical expertise. Some organizations are integrating IT more tightly into business functions like Marketing and Operations by embedding IT staff within the business function.
- Talent management: New customer-centric roles and objectives require a different mix of skills and abilities than traditional IT roles. Communication, business knowledge, and entrepreneurial spirit are more important than in the past. IT leadership is focusing more on the chemistry needed for team members to collaborate effectively with external and internal customers, and less on technical skill alone.
- Vendor relationships: Customer-centrism impacts needs for and expectations of external vendors. Some IT organizations are re-evaluating their outsourcing strategy to bring activities that provide competitive advantage back in-house. Vendors are generally expected to bring a greater understanding of the business, and be able to connect their solution to the overall business goals.
Customer-centric IT has important implications for technology sales and marketing:
- As IT becomes more connected and embedded with business functions, they’ll become more involved and influential in the buying process. Cloud-based solutions have targeted the business function as the primary decision maker and gone around IT, seeing the function as a road block. But organizations and their IT departments have begun to realize the downsides of each department selecting their own solution – they end up with less than the sum of their parts. As with any pendulum swing in the market expect, IT to once again become involved earlier and at a more strategic level. The business will increasingly view IT as a partner rather than an adversary.
- New roles and organizational structures mean that the individual personalities that make up the IT function are changing. Messages and creative that resonated with a traditional IT buyer need to shift to be compelling to the business-focused, entrepreneurial mindsets of the customer-centric IT organization.
- Technology vendors need to understand how their buyer (either as a segment or at the individual organization level) views the IT organization, especially which aspects of IT are sources of competitive advantage and which are commodities. The value proposition and message for a technology that contributes to competitive advantage will be different than one that is a commodity. What constitutes a competitive edge will be different for a pharmaceutical company than a bank.
- Technology vendors can build relationships by helping IT transition to a customer-centric orientation. Through thought-leadership and content marketing, vendors have the opportunity to help IT better understand the end customer or navigate the implications for organizational change.
Technology marketing and sales organizations that recognize the shift to customer-centricity now will be in advantageous position to differentiate from competitors and help IT navigate this transition. Take the time now to understand what customer-centricity means for your target audience and your offering.
The dynamics of today’s IT decision making
Over the past five years, some technology marketers have lost sight of one of their most important audiences – the IT department. The rise of cloud applications, mobile, IT consumerization and BYOD made many technology vendors believe that the IT department was no longer relevant. They envisioned end-users going directly to the technology providers they wanted to use and leaving IT behind to tend to a largely abandoned infrastructure. Looking back, these beliefs about the market followed the usual technology hype-cycle of over inflated expectations and a trough of disillusionment. Today we are in the slope of enlightenment and IT plays a critical role in bringing these technologies to meaningful levels of productivity.
Two broad assumptions drove predictions of IT’s demise: 1) The IT department was threatened by the new technologies and would resist the changes they brought because it was afraid of losing its power in the organization. 2) Having functional departments directly acquire the technology they wanted would improve their productivity and time-to-market performance. These two assumptions turned out to be off-base.
IT’s resistance to change
The IT function is more conservative than other functions such as the marketing and sales teams. But that doesn’t mean it is resistant to change. Cloud and mobile technologies have freed IT from some of the mundane aspects of keeping the infrastructure up and running and enabled IT to focus on the business value it brings to the organization. Pick up an IT trade journal such as CIO magazine and you find far more articles about how IT can add value to the business by better meeting the needs of internal and external customers than you will about technical issues.
On a more tactical level, the talk about IT’s unwillingness to change overlooked a basic truth about the IT department: At heart they are the “geeks” who find technology so interesting that they decided to make a career out of it. New technologies are on their radar screen well before anyone else’s. By the time another department brings at technology too their attention they have already been thinking about the benefits and drawbacks. In a similar vein, resistance to new technologies is often driven by the legal and compliance department that sets the policies the IT department must follow in terms of data security.
Going direct wasn’t a panacea
It turns out that the best application or technology for an individual or functional department isn’t always the best for the company overall. It’s true that by selecting their own systems functional departments are more likely to get the functionality they want and get it sooner. However, these benefits are often off-set by drawbacks from an enterprise-wide perspective.
Effective CRM, SFA, analytics and big data applications requires integration across multiple enterprise systems. Point solutions that functional departments acquired on their own don’t always integrate with other systems as promised creating silos of data across the enterprise. Some departments find that their cloud systems weren’t as easy to manage as they expected and ended up relying on the IT department which creates an adversarial situation where IT was supporting applications it didn’t have a role in selecting. Functional teams didn’t fully factor in how bandwidth would affect their applications performance. Data security requirements cascading down from the legal department resulted in so many restrictions on personal devices that many BYOD programs have stalled.
Better technology decisions
The dynamics of enterprise technology decision making have changed for the better. IT and functional users sit at the table and share in decisions about which technologies make the most sense for the organization. Advances in technology have enabled both sides to focus on the business benefits of technology. National headlines make everyone aware of the security risks that must be considered with any new technology. As a result of these trends, organizations are making better decisions than when one side of the house had a disproportional influence on the decision.
For many enterprise technologies, the primary audience from a sales and marketing perspective should be the functional departments that will get the most benefit from the application. However, technology marketers forget about the IT department, or worse, treat them as a road block to get around, at their own peril. Although the message, value proposition and channels may be somewhat different, savvy marketers recognize the partnerships that exist and look to make connections with both sides of the house.
Why does the adoption rate of many new enterprise technologies fall short of expectations? The answer is often simple: The market isn’t ready. It may have an interest in the technologies and understand the potential benefits but practical realities prevent the market from buying. Understanding these barriers will lead to a more accurate market opportunity assessment, and improved adoption rates.
A lack of technical sophistication
Technology vendors often overestimate the technical sophistication of their target market. They approach prospects expecting to compete with vendors in Gartner’s Magic Quadrant but find themselves competing with Excel or unsophisticated legacy programs. Many companies, even Fortune 1000 companies, use simple applications for important aspects of their operations. For prospects in this situation, a robust solution with advanced functionality is too great a step forward. They worry about the amount of functionality they will use and about the ROI of a solution that is far more expensive than what they use today. And they can justify to themselves that what they use today works, “well enough.”
Vendors that succeed within these market dynamics typically have one or more of the following: A sales and marketing approach that focuses on understanding the needs of the customer and/or on brand trust; a “light” version of their product that lets customers build up to a full solution; or a cloud option that provides customers with key functionality while reducing their risk in terms of financial investment.
Conflicts with existing business processes
A general misalignment of a technology’s functionality and existing business processes will impede adoption. The days of excessive solution customization are gone. However, any new technology must fit with how a company does business. For example, if the sales and marketing teams don’t have processes already in place for sharing information and collaboration, they are unlikely to come together around the purchase of a new CRM system.
Misalignment can also stem from the benefits technology vendors choose to stress in their sales and marketing efforts. The original marketing of business intelligence applications provides a good example. BI vendors initially marketed the benefits of executive dashboards, drill downs and real time alerts to the C-suite. These hypothetical benefits did not match the realities of how most companies are managed. In healthy organizations the C-suite makes long-term, strategic-level decisions: They need summary information and trend data, not information on day-to-day events and processes. The C-suite hires VPs and directors to run day-to-day operations. It is these individuals that require analytical tools, dashboards and real-time alerts. As a result, empowering VPs and directors to make better decisions resonates more with the C-suite than the idea of an executive dashboard. Vendors that understood this nuance developed more effective sales and marketing platforms than their competitors.
Key questions for your business
Understanding your market’s level of sophistication, existing business process and existing solutions can help you more accurately forecast market opportunity and adoption rates, create compelling communication, and identify qualified leads. In addition, communicating an understanding of your prospects’ realities demonstrates a trait that consistently ranks at the top of the list as a differentiator in win/loss analysis: The vendor understands me and my business.
Answering the following questions will help you understand the degree to which your products, sales and marketing are aligned with the market.
- Does your technology match the way people work? Are you selling just a technology or do you need to sell a change in business processes as well?
- Are you stressing the right message to the right individuals with your marketing efforts? Are your marketing and sales efforts aligned with the current mind-set of the market?
- Can your sales reps recognize and adapt to the differences between replacing a simple solution vs. a direct competitor?
If you can answer these question, your customers likely feel that you truly understand them. If you find it difficult to answer most of these questions, you should develop a strategy for filling these information gaps about your market.
Revolutions in Data Analytics
The Independence Day holiday is a good time to talk about revolutions. We are all inundated with stories about big data and analytics revolutionizing how companies use data to run their businesses. As useful and powerful as these tools are turning out to be, the biggest data analysis revolution of all time arguably took place in 1786 when Scottish Engineer William Playfair invented the bar, line and pie chart That is not a typo: We have been using the same tools to visualize data for over 200 years.
Playfair’s goal was to make it quick and easy to understand large amounts of data: “Men of great rank, or active business, can only pay attention to general outlines. And it is hoped, that, with the assistance of these charts, such information will be got, without the fatigue and trouble of studying the particulars of which it is composed.” The blog Seeing Complexity has some examples of Playfair’s charts.
Playfair’s charts have stood the test of time with few challenges to their dominance. PowerPoint and its predecessors have enabled analysts to add colors, shading and three-dimensional aspects to these charts. But these are simple refinements to Playfair’s basic design. Today design experts argue that the elements draped over Playfair’s chart detract more than they add by contributing clutter without additional information or insights. Infographics have added novelty to the visualization of simple data but have not enhanced the amount or type of information conveyed.
The reign of Playfair’s charts looks safe for the foreseeable future. Even in today’s world of unstructured, big data and analytics platforms the insights gained still have to be conveyed to decision-makers in clear easy to understand formats that highlight the big picture without getting bogged down in the details. Data are aggregated and analyzed by state of the art technology, but the executive team is likely looking at the output in a 200 year old chart.
Marketing to the evolving IT organization
Two recent articles in CIO Magazine feature companies (Yum Restaurants, Quintiles Transnational) in which IT departments are taking on new roles in order to more effectively serve their organizations. With a focus on what’s new and noteworthy, these articles profile departments that are leading their peers in reorganizing and redefining how they provide value. Such a shift has important implications for the value propositions, messages, and creative aimed at this audience.
These profiles may tempt B2B technology marketers to envision their IT prospects as innovative, business focused problem-solvers instead of the internally focused risk-averse technicians of yesteryear. We advise some caution before jumping on the bandwagon. As in any market, it’s misleading to define IT as a homogeneous group. The reality is that IT organizations—and the leadership and staff within them—span a continuum in terms of how they define their mission, their goals for the future, and the mix of personalities and decision making styles. Based on Isurus’ extensive research with IT decision makers over the past 10 years, it is true that most IT organizations are in transition. Where they are in the transition and what they are transitioning to/from varies; but they are all undergoing change.
As important as it is to understand the evolving goals in IT organizations, it can be equally insightful for marketers to understand the factors that mitigate their ability to achieve those goals.
- Organizations typically make investments that are consistent with how their performance is actually measured; It is useful to understand whether IT’s performance is assessed using traditional metrics or if those metrics reflect new goals.
- Industry-specific needs also influence the pace of change in IT. Retailers typically change more quickly than financial institutions due to differences in organizational culture and regulatory environments.
- Organizational culture and leadership personality play a significant role in how much or how quickly an IT department evolves.
What does this all mean for B2B technology marketers? Recognize and embrace the diversity within IT organizations. Take a close look at the pace of change in your target audience. Understand both their evolving goals and the barriers they face to achieving those goals. Be prepared to repeat steps 1-3; change is the only constant.