The Foundation for Great Marketing is Great Data

Data is key to all your marketing efforts. Whether it is segmentation, personalization, lead scoring, lead routing, or marketing analysis, if you don’t have clean and consistent data, your efforts will be built on the shakiest of foundations. However, when thinking about your marketing automation efforts, data management can often be an afterthought.

However, some minimal upfront efforts to understand and improve the quality of your data can greatly improve your effectiveness as a marketer.

Current Database

First, you need to understand your current database. There may be a significant amount of data in your database, but unless it is data you can work with, it will not be adding value to your organization. Some simple analysis should give you a good sense of your current state:

- Growth and Total Size: The simplest of metrics; analyzing both the total size of your database and its growth over time gives you a clear sense of what you’re starting with. Net new contacts add to your total, while bouncebacks, and unsubscribes detract from it. In this measurement, be sure that you are truly measuring unique contacts, without any duplication. The overall database size should be growing in a healthy manner, although growth rates can vary depending on the growth rate of your company and your industry.

- Active/Inactive: Of equal importance to size of your marketing database is the analysis of what percentage of your database is active or inactive. A basic definition around “active”, such as a certain number of emails opened or clicked, visits to the website, or form submits will give you an objective definition of who is active. Those who are inactive may have “emotionally unsubscribed”, and are unlikely to be future buyers. It is more important that the active component of your database is growing over time than the overall size.

- Completeness: Each field that is of importance to you should be analyzed for its completeness. In many marketing databases, key fields may be only 30% or less complete, which leads to challenges in using those fields for marketing efforts. If your analysis shows that fields are less complete than ideal, you may want to use progressive profiling to add data to those fields

- Consistency: Even if a field is filled, if the data is inconsistent, it can be very difficult to derive value from it. Fields like Title, Industry, Country, State, or Revenue are very often extremely inconsistent as the data can be input in a wide variety of ways. Analyze each field for the breakdown of what values are in that field and their percentages to see if the data is generally consistent or inconsistent.




Some marketing automation platforms are able to perform this kind of analysis, but there is a lot of variation in the industry, so ask the tough questions if you are considering a marketing automation investment as this analysis will be key to your success.

Data Sources

With your own marketing database quality understood, you then need to begin understanding your sources of data to understand what will make your data challenges worsen if not controlled. Marketing data comes from many different sources, each of which has its unique opportunities and challenges.

- Other Systems: Marketing often sources data from CRM systems, data warehouses, or customer data masters. The data from these systems often must be brought in on a nightly (or more frequent) basis, and integrated into your marketing data. In many cases, there is limited opportunity to change the format or quality of the original data, and it must be dealt with on import automatically each time it is imported

- Continual Sources: Web forms, tradeshow leads, webinar registrants, and trial downloaders contribute a steady flow of data to the marketing database. The continual nature of these sources means that as a marketer, your database is being updated 24 hours a day, 7 days a week. This means that data cleansing must be done continually, and inline, rather than as a batch process once or twice a year

- Controlled vs Non-Controlled: Many of the sources you deal with are not sources that you are able to control. Lists from tradeshows, business cards, and many web forms are not sources that you are able to control, so the data from them is of varying quality and varying standardization

Given that you, as a marketer, are dealing with a variety of data sources, many of which are out of your control, and many of which are operating 24x7, keeping the data clean and consistent can be a significant challenge. The best way to approach this is to build a “contact washing machine” that standardizes and normalizes your data. Each time data is touched, whether from a web form, a list upload, or from your CRM system, it should flow to the contact washing machine.

Again, this is an area to ask tough questions in if you are looking at making an investment in lead management software as it makes a significant difference to your success. Look for contact washing machines that are a single, centralized point of data cleansing, and can handle standardizing and deduping data fields from industry to title to revenue. The best option is to have a pre-built structure out of the box, that you can then modify to meet the exact requirements of your business.


Data and the User Experience

In thinking about data, there can be a temptation to burden your audience of prospects with the data requirements of your marketing database. This is never a good idea. Many studies have shown that the more fields you add to your web forms, the more likely you are to see users drop off and not fill them out. Similarly, the more you restrict the input options that you provide to your audience (such as only allowing drop-down select lists for an individual’s job title), the more frustrated your audience will become.

The best option is to approach the challenge in two ways. Progressive profiling can be used to ask for a minimal amount of data at each interaction, never ask the same question twice, but continually add to a modular profile. This allows you to minimize the number of fields being asked per web form, and maximize the conversion rate. For the data itself, given the user frustration added by constraining their options, and the fact that many sources of data are beyond your control anyway, it is often better to allow free-form data while managing its quality via a contact washing machine once it enters your marketing database.


Data as a Foundation for Great Marketing

Today’s best marketers are building their creative campaigns, precise segmentation, accurate lead scoring, and relevant personalization on a base of great data quality. In fact, when top CMOs talked about their marketing dashboards, the focus on quality data was key to each of their successes. Whether you have made a marketing automation investment, and are looking to maximize the return you get from it, or are considering a marketing automation investment and want to know the right questions to ask, data should be front and center. It’s the foundation upon which everything else in marketing rests.

(*this post was originally posted on the Focus.com marketing community)

Loose Coupling and Analysis of the Marketing Process

When analyzing the flow of leads through your marketing organization, and into your sales organization, how you design the stages in the process has a significant impact on both how you are going to be able to analyze it, and how you are going to be able to optimize it in the future. Without the ability to both analyze and optimize a process, you will find that errors begin to creep into the process due to the lack of visibility, and your ability to adapt the process as your business changes or grows is minimal.

The best approach, when you have a hand-off between one team and another, is one that is “loosely coupled”. Your marketing team, for example, may pass marketing qualified leads (MQLs) to your sales team. However, what the sales team accepts should not be termed the same thing – MQLs – as this does not allow the system to account for, and measure, a drop-off in the acceptance rate. Instead, these leads that are accepted by sales should be termed differently – in this case Sales Accepted Leads – SALs.

Even in a system where your current design parameters state that 100% of MQLs should be acted on by sales, you should still name and handle them separately. The reason for this is two-fold. For one, no system involving people can ever operate at 100% accuracy. Some of your lead will slip through the cracks due to bad data, absent employees, or inattentiveness. Without having both MQLs and SALs to measure, and thus a SAL/MQL acceptance rate, it is not possible to measure how close to 100% your system is operating at.

The second reason to avoid the tight coupling that is implied by having the same name in subsquest process stages is that most marketing organizations will change their processes over time. Perhaps your current design specification is a 100% acceptance rate of MQLs within the sales team. This may change in a quarter’s time if you decide to open up the funnel a little bit, and pass more leads to your sales team, while allowing them to selectively choose. You may reduce the design parameter to 60%. Without the “loose coupling” that having unique naming provides, it will require a full change of your marketing funnel process just to shift this one parameter. Instead, build in the flexibility up front by having the pre, and post-handoff leads named separately.

The example of MQLs being passed to sales is an obvious one, but this becomes a more interesting challenge when the names are not as obvious. For example, if you have an inside team focused on lead generation. They would take a lead at some level of quality, place a call, confirm interest, perhaps budget and authority, and deem the lead ready for the field sales team. If this team is part of the marketing organization (in some organizations, this team is part of sales), then you might wish to call the output of this team’s work an MQL. However, the question is, what is the input to this team?

Obviously, you will be scoring the leads prior to handing them to this team, so you might call them “Qualified Inquiries” to differentiate them from the raw inquiries you see on your website. The Qualified Inquiries that are then picked up by the inside team might be called “Qualified Inquiries Accepted” in order to allow you to manage the handoff between your marketing campaigns team and the inside team and allow that handoff ratio to be adjusted as needed.

The loose coupling provided by having unique names for each relevant stage of the buying process allows you to both analyze the operation of your process and also make adjustments as needed. Some upfront planning to define sufficient handoff points to allow the right amount of adjustment later can save you significant future rework.

Fit, Engagement, and MQLs: Mapping the Lead Handoff to Sales

Marketing organizations looking to only hand qualified leads over to their sales teams are faced with an interesting analysis challenge. Whereas it might seem to be a simple task to look at implicit data on a prospect and understand their engagement, or look at explicit data on a prospect and understand their fit, the reality is that this is often a relatively difficult task.

The first task is to look at the raw data in order to define a score between, say 0 and 100 points. This is not as simple as more activity leading to a higher score; some areas of activity may in fact be worth more score than others, and time needs to be taken into account in order to ensure that scores do not grow indefinitely over time. The machinations of this scoring algorithm, however should be kept separate from the sales organization.

For a sales organization to be comfortable building a process, they need a stable definition to be applied to the leads that are sent their way. This is where the fit/engagement matrix is highly useful. A value for the lead’s “fit”, in other words their title, industry, and size, can be mapped to a standard definition of A, B, C, D, where A is a high fit, and D is a low fit. Similarly for a lead’s “engagement”, or their activity on the website, a standard definition of 1,2,3,4 can be applied, again with 1 representing high engagement and 4 representing a low engagement.

The sales team can then understand leads as A1s, C3s, or B4s. The underlying scoring definition of what earns a lead points, how those points are adjusted over time, and which range of points maps to the each rank, does not need to be visible to the sales team at large. A core group of key individuals within sales and marketing can debate the definitions and make necessary adjustments each quarter.

With a clear definition of what makes each lead rank, the discussion can then progress to which leads should be passed from marketing to sales, and to which sales team if there are multiple teams involved. A1 leads will obviously be passed directly to sales, likely to a field sales force, but a mapping is needed for where each other lead rank goes. Some may be passed to an inside sales team, some may be passed to a partner channel, and some may be held back to be further nurtured. The set of leads that are passed to sales from marketing are deemed marketing qualified leads (MQLs). This higher level definition is useful in looking at a higher level view of your marketing analysis.

There are two key questions that these efforts in lead scoring allow you to tackle in analyzing your marketing programs:

Does our scoring accurately correlate to a higher propensity to purchase?
- A lead scoring algorithm should be continually revisited in order to ensure that a higher score actually correlates with a higher propensity to purchase, based on both fit and engagement.

Which leads are worth sending over to sales based on the sales team’s ability to engage them in relevant conversations?
- Adjustments in your marketing, sales, and channel mix can mean that you may
wish to send more leads or less leads to sales. This adjustment comes into play
as you adjust which leads, A1, B2, C3, etc, are sent to sales as Marketing
Qualified Leads (MQLs)


In order to better enable analysis of what is working and what is not, it’s a good idea to keep the lead score and lead rank tracked. As these are values that change with time the best way to do this is to stamp the values at the point in time that the lead is passed to sales. This value pair can then be analyzed against later in order to understand whether the score and rank at that moment in time accurately indicated an intent to purchase.

Setting up a lead scoring and lead handoff process in a way that allows you to both analyze and adjust it as you learn and your business grows, sets you up for long term success.

Lead Handoff and Sales Measurement - Video

Scoring leads to determine which are qualified for sales is only valuable if the sales team works with those leads appropriately when they are handed off. This is complicated by the fact that in many cases, a sales attempt to connect with a lead can result in ambiguous outcomes, like leaving a voicemail, or discovering that the prospect is interested, but suggests speaking again in three months.

In this quick video, Eloqua’s Director of Marketing Operations, Chris Petko maps out the key elements of a process for handing leads to sales, providing sales with a way to easily take action on a lead, and then automatically handing each of the lead dispositions that are likely to happen.



(if the above video doesn't load, please click here for the lead handoff and sales measurement video)

The ability to select which leads, by both fit and engagement, are qualified for sales allows very flexible control of the flow of leads to sales, so the flow can be increased or decreased based on the propensity of the leads to close and the size of the sales force. Similarly, creating a task for sales for each lead allows very rigorous management of the overall process, as the task completion can be managed and measured very carefully.

This all follows from effectively defining which leads are truly ready for sales. This was covered very well in a recent video on lead scoring best practices that is worth watching if you missed it.

Marketing automation is of course a key element in handling the lead dispositions, as Chris highlights in the video. For each disposition option on the task presented to sales, a marketing automation program can handle the lead, nurture them as appropriate, and monitor them for signs of renewed activity.

Enjoy the video, Chris lives and breathes marketing operations, and truly knows his stuff.

Data and Predictions in B2B Marketing

I recently read an interesting book on predictions - things like weather, economics - called "Apollo's Arrow" by David Orrell. In the book, he talks about a number of challenges to accurately predicting future events. There are many challenges, but foremost among them are the data you use as a starting point, and the model you have for how events will unfold.

In predicting the weather, for example, a three dimensional grid of temperature, pressure, and humidity values is constructed as a starting point. From here, various computer models attempt to forecast how weather patterns, temperatures, rain, and wind will occur. The resulting predictions (unfortunately still very inaccurate) are challenged by both the inaccuracy of the starting points and the model used to predict an outcome.

Interestingly, an individual model can vary greatly in its ability to predict different outcomes. Temperature may be relatively well predicted, but rain may be no better than guesswork.




In reading the book, I was reminded of marketers' challenges in using lead scoring to predict which leads are good enough to be passed to sales. We have similar elements; the underlying data - in our case digital body language - on the prospect's activities, and the model we use to score leads and determine which is a qualified lead.



This is interesting though in that we are looking at one individual and deciphering their intention to purchase. However in B2B marketing it is a business that purchases, not an individual. Much like predicting temperature vs predicting rain, one aspect of the buying process prediction that often leads to very accurate results is predicting the business that will buy, rather than the individual. Looking at the businesses visiting your website gives very intreresting clues as to where a vigorous buying process is happening.


If you see multiple visitors on your website from one company, they are doing deep investigation, and are using compelling search terms when finding you on Google, you know that there has likely been an internal event at that organization that has caused a group to begin investigating your solutions.


Of course in this scenario, you may or may not know the individual who will guide the final purchase decision. If you do know most of the key members of the team who would be involved in a buying decision, you just need to present to your sales team with the information that the business in question is clearly showing buying signals. You can do this through building account traffic light dashboards in your sales team's CRM system, or other sales enablement techniques.



However, if you don't know the key individuals who would be the decision makers on a purchase of your solutions, you can focus your efforts on what you do know - that a buying process is under way at that organization. Knowing that, a role-based discovery service such as Reachforce can easily capture the names you require and get your sales team in touch with them.


Much like predicting the weather, predicting buying behavior can be challenging and imprecise. However, even being able to predict key indicators like the fact that a buying process is underway at a specific organization adds tremendous value to your sales team.

What is B2B Marketing?

What exactly defines Business to Business (B2B) Marketing?

It’s an interesting question, as marketing is a discipline that is common across both business to consumer (B2C) and business to business (B2B) organizations. However, beneath the surface, there are significant differences in how B2B and B2C marketing is done in today’s environment. It’s worth exploring what B2B marketing entails.

Let’s look at a few of the areas that differentiate a B2B buying process:

Information Exchange

In B2B marketing, you are often dealing with a buying organization that requires a significant amount of information during their buying process. Unlike in many consumer marketing situations where the need for clothes, food, or cleaning products may be well understood, in B2B marketing, that may not be the case at all. Early stage education on industry transition, technology changes, or regulatory changes can be needed in order to best understand why your solution’s category even exists in the first place.

This need to exchange information continues throughout the buying process. Buyers, when convinced that a potential solution exists to their business challenge, will then need to know which solutions to evaluate, what criteria to evaluate them on, and what evidence exists that one solution is better than the others. B2B marketers need to understand where in this education process their largest marketing challenge exists in order to better educate the buyer.

Social media becomes a critical part of this information exchange in a B2B environment as social media forms a great medium through which to educate, converse with, and build relationships with prospective buyers who may be interested at a point in the future. Over time, a great social media strategy in a B2B organization will improve market perceptions of your organization in ways that other brand investments never could.


Multiple Buyers

In B2B marketing, the most common situation is one in which multiple buyers are involved. Each buyer may take a different role in the buying process, whether it’s a technical evaluator, decision maker, or economic buyer. Each of these buyers needs to be educated at each stage of the buying cycle to ensure that they facilitate moving things forward. This leads to a need in B2B marketing for a significant amount of content. Each buyer in the buying committee, at each stage of their buying process, has specific educational needs. Mapping marketing content to the buying cycle is key in ensuring you have the right assets available for each of the buyers involved.

Whereas in B2C marketing, there may be a husband and wife both involved in a buying decision, the unique roles that are played by B2B buyers allow very clear differentiation of buyer roles. By carefully monitoring buyers’ digital body language, B2B marketers can identify buyer roles based solely on their actions. This allows messaging to be catered precisely to the unique needs and interests of each buyer role.


Sales Involvement

The complexity of most B2B transactions means that there is usually involvement of a sales team prior to a deal being finalized. This may be an inside sales team, a field sales team, or a channel partner’s sales team, but the direct involvement leads to another unique aspect of B2B marketing. One of marketing’s main roles in a B2B organization is to provide sales with a steady flow of qualified leads. Given the length of the buying process, this is a challenging undertaking. First, the marketing organization needs to understand the digital body language of buyers in order to see indications of who is ready to buy, both on their main web properties, and also as seen being referred in through the social media “periphery”.

With this insight, B2B marketers can then establish a lead scoring system that identifies and ranks prospective buyers. Those that are ready for sales involvement can be passed on to sales, those who are not yet ready can continue to be nurtured until they do show the signs of being ready. This active management of the top of the marketing funnel leads to unique challenges for B2B marketers, as there is a need for rich thought leadership content of interest to prospects at the top of the marketing funnel in order to effectively nurture leads until they are ready to consider a purchase.

Marketing needs to work on not only a steady flow of qualified leads to sales, but also needs to provide the insights needed to sell better through sales enablement techniques. Sales enablement involves providing insights into which prospects are actively interested, who within an account is a key influencer, and which accounts within a territory should be focused on.

Length of Buying Cycle and Challenges for Marketing Analysis

The length of the B2B buying cycle also causes significant challenges for marketing analysis. Given that buying cycles can last months or quarters, if not years, the analysis that can be performed on marketing’s effectiveness is very different. B2B marketers must take a top-down approach to marketing analysis that looks at an overall lead funnel, where each prospect is within it, and what changes in the lead funnel have been made within the last period of time.

When looking at individual campaigns, each campaign can be analyzed, or even A/B tested against results, but often should only be analyzed against tactical results such as the creation of marketing qualified leads or inquiries of a certain level of qualification. Analyzing individual campaigns contribution to revenue can only be done in B2B marketing with the acknowledgement that many campaigns will have contributed to one revenue event, and that the resulting revenue must be attributed across the contributing campaigns.

Concluding Thoughts on B2B Marketing

As today’s buyers continue to evolve, and gain more of their education online, through social media, or through any other form of online information exchange, the role of the marketer continues to evolve. Whereas the classic role of marketing (as described by Peter Drucker), to know and understand the customer so well that the product or service fits them and sells itself, has not changed, the techniques for doing that in a B2B scenario are different from those used in a B2C scenario.

Lead Scoring Best Practices

I sat down with various folks on the Eloqua Customer Success team to hear their experiences on what it took to build out a highly successful lead scoring system. Jocelyn Brown (@jocebrown), Chad Horenfeldt (@chadhorenfeldt), and Adrian Chang (@adrianchang) are the folks who help clients with implementing lead scoring at organizations of various sizes and within a variety of industries, so they have the experience to know what it takes to achieve success. Here is their take:




Some key takeaways:
- get buy-in from sales management in order to best align goals
- use a matrix of A-D for fit and 1-4 for engagement
- define what will happen with each lead, based on that matrix, from lead nurturing to sales hand-off
- define an SLA with sales on how long is allowed for follow-up
- don't be shy about lead clawback if too much time passes
- sales cherry-picking leads is a sign of mis-alignment between marketing and sales
- lead scoring is one of the most valuable things a B2B marketing organization can do

I hope you enjoy the video, I always learn a lot chatting with people like Jocelyn, Adrian, and Chad, as they deal with organizations who are wrestling with these challenges on a daily basis.

Marketing Automation Weekly Wrap-up - 2009/08/07

There are so many great writers in the field of demand generation and marketing automation out there that create fresh and interesting content each week. Some are entertaining, some are practical, some are thought provoking, and they are all worth a read. Here are some of the posts I have enjoyed over the past week or so (in no particular order):





Tom Pick (@tompick) from Web Market Central questions the quest for "Return on Investment" in social media with the concept of "Return on NOT Investing". An interesting read and definitely another way of thinking about the opportunity costs involved:
http://webmarketcentral.blogspot.com/2009/07/social-media-roi-vs-roni.html





The Savvy B2B Sisters (@Savvy_B2B) provide a detailed guide on the how and the why of writing eBooks for B2B marketing and thought leadership: http://savvyb2bmarketing.com/blog/entry/194051/5-things-you-should-know-before-you-write-an-ebook





Robert Lesser from Acquiring Minds gives an entertaining (but surprisingly accurate) run-down of the Top 10 Signs that Sales & Marketing are Mis-Aligned:
http://www.directimpactnow.com/leadgentools/blog/2009/07/10-signs-that-sales-marketing-are-mis.html







Chad Horenfeldt (@ChadHorenfeldt) from Anything Goes Marketing posts a very comprehensive set of ways of using Twitter for B2B marketing and sales:
http://anythinggoesmarketing.blogspot.com/2009/08/tips-on-using-twitter-to-boost-your.html




Brian Carroll (@brianjcarroll) from Start with a Lead reviews the book “Professional Services Marketing” that talks about the marketing and selling of professional services, and why it is that clients buy:
http://blog.startwithalead.com/weblog/2009/08/good-advice-for-growing-your-company-from-industry-experts.html




Laura Ramos (@lauraramos) from B2B Marketing Posts dissects a stat that shows that social media use is soaring in B2B marketing, and makes some great comments on "use" vs "success" in social media for B2B marketing:
http://b2bmarketingpost.com/2009/08/04/social-media-use-soars-among-b2b-marketers-really/




Mike Damphousse (@damphoux) from Green Leads made a compelling argument for lead quality over lead quantity. Mike's coming at it from the appointment setting business, but the argument still holds water in regular demand generation circles. Quality will pretty much always trump quantity:
http://www.damphousse.org/2009/07/sales-ready-leads-quality-vs-quantity.html





Steve Kellogg (LinkedIn) from Crowds2Crowds wrote an entertaining obituary for batch & blast marketing. I can't agreee more, the sooner we move away from batch & blast campaigning towards truly understanding our prospects, the better we all do. RIP batch & blast: http://crowds2crowds.blogspot.com/2009/08/for-those-still-using-batch-blast.html






Britton Manasco (@brittonmanasco) from Illuminating the Future writes a very thought provoking post on whether the "Guidance Economy" is the next wave. Lends a new imperitive to thought leadership initiatives:
http://www.brittonmanasco.com/2009/07/confronting-the-guidance-imperative.html





Jep Castelein (@jepc) from Lead Sloth breaks apart the various types of "free trials" that are used in B2B marketing and discusses how they can best be used and what they are appropriate for. Worth thinking about before a mad rush to offer a free trial:
http://www.leadsloth.com/blog/free-trials-arent-what-they-used-to-be/






Mac McIntosh (@B2B_Sales_Leads) from Sales Lead Insights posts a comprehensive list of decision criteria for lead qualification from demographics and firmographics to activity and interest profiling. A good discussion starts in the comments:
http://www.sales-lead-insights.com/2009/a-list-of-b2b-lead-qualification-criteria-by-category/

Data Analysis in Marketing; What Google and the Flu Can Teach Us

I saw an interesting tool the other day from Google, that analyzed raw data on searches related to the flu in order to predict the severity and timing of flu outbreaks. Available at http://www.google.org/flutrends/, this tool is an interesting example of approaching data in a unique way in order to understand a problem.

Whereas an individual person searching for a flu-related topic is clearly not a diagnosed flu victim, the correlation between those searches and an actual outbreak is quite good, and more importantly, the data is available much faster than the medical diagnoses precisely because it is not relying on a properly diagnosed flu victim as the base data point it works from.

As we implement lead scoring algorithms, and other predictive approaches within our marketing automation systems, we face a similar challenge. The best way to look at whether we have scored the leads the right way is to look at whether the leads we passed to sales became qualified opportunities and eventually closed revenue. However, similar to the medical diagnoses in the flu example, this can take a significant amount of time. However, the raw data can show us some very interesting trends and give us immediate insights.

When you have built out an initial algorithm, incorporating the best practices for lead scoring, the simplest thing to do is to pass your entire dataset through the algorithm to see how they would score. This “bottoms-up” look at the data gives a very quick view of the potential results. This technique is best used when looking at the explicit score (the “who” that indicates the right buyer in the right organization) rather than the implicit score (the “how interested” that indicates the level of current buying interest. The reason for this is that the “who” is not likely to change over time, while the “how interested” will obviously vary significantly over time.

With your entire database scored through your new algorithm, the results will tell you some very interesting things.

- Were the final numbers what you expected? If you scored 100,000 contacts on the explicit dimension of lead scoring, and only 0.1% ended up as A leads, was this what you would have anticipated? If you were expecting significantly more, it could easily be a data problem. For example, if your scoring algorithm looks for a key title, such as “Vice President of Marketing”, and you have not cleansed your data, you may miss most, if not all, of the contacts you are looking for. In our own experience, that search returned only 300 results before cleansing, and over 17,000 results after data cleansing to standardize all the other ways of writing “VP. Marketing”, “Vice Pres Mktg”, etc.



- Does the sales team like what they see? If you show your sales team a sample of the leads who scored well in your new algorithm, do they think that these are the right set of leads they should be speaking with? If you show them leads that did not score well, do they agree that these are not leads they would like to speak with? Remember, of course, that you are only looking at explicit information, not buying activity in this example, so it is assumed you would only be passing your sales team these leads when buying activity was detected. Balancing your sales team’s intuition with your objective lead scoring algorithms is as useful here as it is in highlighting flaws in the process through sales “cherry-picking” of leads.


- Does history agree with your hypothesis? When Google looked at their flu data, they compared it carefully with CDC data on actual flu outbreaks to ensure that there were minimal false negatives and false positives. Similarly, your lead scoring results need to match history accurately. If you look at contacts who were scored highly, and who have also been around for a long time, is there a higher number of them who have become customers? It not, what is missing?

Marketing data can be a true gold mine of insight if you use it carefully, much in the same way that search data shows extremely interesting predictive insights when looked at in certain ways.

What insights have you found in your marketing data that surprised you?

Medical Symptoms and B2B Marketing Processes

The medical world is very used to the fact that symptoms such as pain, headaches, and nausea are often the body's way of indicating that something has gone wrong. When a treatment is applied to the symptoms alone, it can mask an underlying problem. For example, regular unsupervised use of antacids for heartburn or reflux disease might mask the symptoms of more serious things such as barrett's esophagus, a stomach ulcer, or stomach cancer.

I was reminded of a similar challenge when a lively discussion ensued on LinkedIn about whether marketing should allow sales to “cherry pick” leads. I had written a post talking about the challenge to the overall flow of the funnel when sales is allowed to cherry pick leads. The natural flow of scoring leads, qualifying them, and then handing them off to sales is disrupted when a sales team is allowed to grab the best leads from the funnel regardless of where the scoring system has placed them.

The group discussing the issue agreed, in general, that the disruption of having a salesperson cherry pick leads was not ideal, however, it had the critical benefit of pointing out flaws in the scoring process. A salesperson cherry picking leads that the lead scoring algorithm has not deemed ready for sales may be an indicator of a deeper underlying issue. Perhaps the scoring algorithm misses certain key activities as criteria, perhaps there are opportunities in verticals outside of where the lead scoring algorithm focuses.

In the same way as medical symptoms are uncomfortable for a reason, to get your attention to a problem, the disruption of the smooth flow of leads caused by sales cherry picking can be seen as a symptom of an underlying problem. Whereas I still feel that sales cherry picking is an undesirable outcome, I do believe that if analyzed as a symptom, it can provide interesting and crucial insights into where a lead scoring process is missing the mark.

Sometimes, allowing a few "breaks" in a marketing automation process is a great way to identify opportunities to improve the overall process. When looking at your marketing team's interaction with sales, look for where you see breaks in the process, and look for processes that would completely prevent or totally mask breaks in the process. Removing a symptom of a broken process, much like removing a medical symptom, may only be hiding a deeper underlying problem.

Marketing Automation - What does it mean?

Consistently, the term “marketing automation” is applied to our industry. I find it a term that is less than ideal when it comes to describing what the industry does, but nonetheless, the term has stuck. I often get the question of “can marketing really be automated” and I think that there’s an opportunity to clarify what aspects of marketing truly can be automated, and what aspects cannot. Also, given that the industry’s growth is surging, there’s an opportunity to look at the dynamics that are driving this desire to automate marketing.

If asked for a definition, I would say:

Marketing Automation is the art and science of automatically managing the targeting, timing, and content of your outbound marketing messages.

Let's look at why.

The Changing Buyer

First, let’s look at our buyers. Over the last decade, their ability to self-educate and manage their own buying processes has increased astronomically. Whether it is through vendor websites, analyst websites, social media, or peer reviews, buyers can acquire the information that they need in order to move towards a purchase decision.

However this transition in our buyers has meant that we as marketing organizations need to work with our buyers differently than we did previously. If we hope to facilitate their buying process, and guide them to consider, prefer, and select the products and services we are offering, we need to provide them with the precise information they need as part of their buying process.

The most critical factor is relevance. If we are able to deliver information that is relevant to the buyer’s role in the buying process, their stage as a buyer, their level of interest, and the areas of decision making of interest to them, we will establish a connection, and our message will get through. If not, our message will be lost in the clutter.

So where does marketing automation come in?

If you look at what is required, we need to first understand each of our prospective buyers individually, then we need to provide a message to them that has ideal timing and content based on their interests and stage in the buying process. This level of precision on targeting, timing, and content is nearly impossible without having a solid underlying platform to work from. The art of marketing, when it comes to creating persuasive, compelling copy, great offers, and elegant positioning cannot be automated, and likely won’t be in our lifetimes. However delivering the right selection of those messages to the right person at the right time is something that can no longer be done without automation.

Marketing Automation and Timing

Marketing automation gives us the ability to work on the exact timeframe of the buyer. This is best understood in the context of marketing initiatives like downloadable free trials. In downloading a free trial, the buyer has indicated that, at that exact moment in time, they are at the stage of their buying process where spending time with a trial is their most appropriate use of time. Your communications, as a marketer, need to reflect this buyer timing in order to best connect with this buyer.

Without automation, if a marketer is to attempt this with batch communications, the more closely one tries to align with the buyer’s timing, the smaller and smaller your batches must become, and the larger your workload as a marketer grows. Only through automation can a marketer effectively deliver a message on day 1, day 15, day 30, and day 90 to each individual prospective buyer.

Marketing Automation and Personalization

As one communicates with prospective buyers, each communication should ideally contain content that is precisely in line with their interests. The best way to do this is with dynamic content that automatically matches content to their interests. However, most prospective buyers will not explicitly declare their interests. If they do, the data is likely to be inaccurate. Marketing automation, by letting you tie web activity into buyer insight allows you to understand buyer interests based on what they do, not what they say.

On top of this foundation of buyer understanding, marketing automation gives you a platform from which to have that insight automatically personalize outbound content. Manual processes to personalize the content would quickly prove impossible, and the impact of not personalizing the content is a significant decrease in its relevance to the buyer.

Personalization and the Sender

However, the content itself is not the only aspect of personalization that impacts the buyer’s likelihood of engaging. Who it comes from is equally important. Recipients are 30% more likely, in most cases, to interact with content if it comes from a known person, rather than from a company. A marketing automation system can automatically have each communications come from the appropriate member of your sales team, building the relationship while increasing the response rate. To send your communications on behalf of 5 or 10 sales people might be possible if done manually, but to send on behalf of 50 or 100 requires automation.

Marketing Automation and Sales

As buyer progress through their own buying processes, they eventually reach the point when they would be willing to talk with someone in your sales team about pricing, contracts, or other elements of the purchase process. Knowing when they have reached this stage involves understanding their digital body language. Signs of buying activity can be seen and with the appropriate lead scoring algorithm, sales ready leads can be identified and passed to sales.

Whereas this analysis of leads has in the past been done manually or with spreadsheets, the need to identify and follow up with leads when they are most ready means that it must be done quickly. Using automation allows marketing teams to objectively and automatically score the leads in their marketing funnel in real time, identifying those that are sales ready and those that are not. Those that are not yet ready can be kept warm over time through lead nurturing, again a process that automation greatly facilitates.


The New Importance of Data

What we’re seeing in the above discussion is a shift away from batch communications that are not highly differentiated to true one-to-one personalization. However, as we do this, and we have marketing automation platforms, rather than people looking at the data to make decisions, the importance of data quality takes on a new priority.

Data, in order to be used by rules for personalization of content, segmentation of lists, and scoring and routing of leads, needs to be clean and consistent. Marketing teams are being tasked with ensuring this consistency is maintained at all times, even though marketing data may be touched by web forms, list uploads, CRM synchronizations, or sales input. The only way to consistently and constantly maintain a clean and standardized set of data is to use automation to manage marketing data quality in-line within the marketing database.


What Can’t be Automated?

Marketing remains as much art as it ever has been, even as the new buyer requires elements of science in automating how the targeting, timing, and content of a message is delivered. Compelling offers, captivating visuals, great positioning, and elegant copy are as difficult as ever to create. Likewise, the understanding of market segments, buyer journeys, stages of a buying process, and what moves a buyer along their buying process still differentiate excellent marketers from merely good marketers.

However, as today’s marketers shift from outbound messaging to understanding a buying process and facilitating it, they can only do so if enabled with a platform that automates the conversations, timing, and personalization needed. That is where marketing automation comes in.

Is Good-Enough-Marketing-Automation Really Good Enough?

Today's post is a guest post from Paul Teshima, Eloqua's Senior Vice President of Customer Service. Paul is the person responsible for the team that drives the success of our clients, and is very hands on in working with clients big and small.

As such, he has been the brains behind many of our innovations on how to tackle various business processes, new approaches to scoring leads, and innovative ways to manage global deployments.

I'm thrilled to have Paul post as the insights he brings are without parallel.

Steve

=====================================

There is a lot of activity and discussion today on best practices in demand generation and marketing automation. Marketers are now realizing they don’t have to build the perfect campaign or program to generate value from marketing automation.

So on one side I am very happy that we are seeing rapid adoption of marketing automation, but on the other side, I know that we need to do more. Marketers may have become happy with “good-enough-marketing-automation”, which is a great place to start, but you need to continue to improve to get the most out of these programs.

Let me give you a couple of examples:

1. From Auto-Responders to a Warm Welcome
Many marketers have seen good results with targeted auto-responder emails (not just "thanks for downloading") once you fill out a form. this is a great tactic and can drive high response rates. But you would be surprised to know that on average 15-20% of your new leads in a quarter receive no communication in the first 60 days outside of an auto-responder.


This is largely due to the fact that your list pulls don't always account for "new leads", but rather focus on specific profile information (e.g. CIO, in New York, in Financial Services).

We have seen rapid adoption of what we like to call a "Welcome Program". This program targets new leads that for one reason or another don't receive any marketing communication due to your segmentation strategy. It can be as simple as 3 emails over 3-6 weeks that provides value-add information on why you should stay interested in your business.

Customers have seen great results with these types of programs as these leads have already raised their hand. Welcome programs can generate qualified leads at a rate of 10-15%. This is the first nurturing program every customer should have.



2. From Lead Qualification to Strategic Account Management
Many companies, small and large have targeted account or vertical strategies that involve lists of thousands of named or strategic accounts. When implementing a scoring program often this targeted list is ignored because how do you setup scoring rules for 3,000 company names, when often the field data varies by record (i.e. IBM, I.B.M. IBM Corp., etc.).

But these leads are actually some of the best leads from an Explicit or Ability to Purchase perspective. You would always call them back. So it is imperative that you include them in your scoring program (note: this may involve data tools and some complex deduplication.)

In fact we have found that 20% of all of our customers use a Named Account List in their scoring program - and many of them also route these leads directly to field sales - reducing delays in the right follow-up, and also cost of generating the quality lead.

It is important to understand that starting simple with marketing automation is definitely the way to go. But instead of thinking of it as a one step process, think of it as an effort in continual improvement. I believe that marketers who take on this challenge, will have more effective campaigns and drive significantly more value for their business.

Analyzing B2B Marketing: Balance Sheet and Income Statement

Consistent in every discussion I have with B2B marketing execs is the topic of analysis. We're all very familiar with the tactical metrics on each marketing type; open rates and click through rates on emails, landing page conversion rates, cost per click metrics, traffic statistics, and so on. However, these metrics fall short when it comes to understanding marketing's overall contribution to the performance of the business.


Much recent writing has focused on a campaign-up view of the world, with analysis focused around an attempt to determine the return on investment for each campaign. These ROI or ROMI analysis frameworks tend to run into challenges in a B2B marketing environment as the buying cycle is often of significant length, and influenced by many touch-points.


An alternative, and much more actionable framework, is a top down view that uses a "balance sheet" and "income statement" view of the marketing world to understand marketing's overall effect on top-of-funnel activity. Within this top-down view, marketing actions and campaigns can facilitate buyers moving from one stage in their buying process to another, but the complexity of each campaign's individual influence is smoothly aggregated into an overall view that shows the current view of the top of the funnel, and the transitions that have been made over the last period of time.


The first step in looking at this view of the B2B marketing world is to map the buyers' buying process. Each step from education and awareness through to vendor discovery and validation should be understood and mapped, as these are phases that are influenced by marketing, and thus highly relevant in an overall marketing analysis picture.


In order to understand which buyers are at which phase of their buying process, the techniques of lead scoring can be used in order to map each prospective buyer to their individual stage of the buying process by looking at their digital body language.


With this in place, it is possible to build a "balance sheet" view of the B2B marketing funnel. This is a moment-in-time view of where leads are in the funnel, much as a financial balance sheet is a moment-in-time view of where dollars are in an organization at the end of a reporting period.


To have this view relevant and accurate, it is of course necessary to ensure that lead scores degrade over time. Buying interest is, in most cases, a transient phenomenon, and if a lead has not turned into a sales qualified opportunity (SQO) within a certain amount of time, it likely will not, so ensuring a time-based decrease in score is key.


With a balance sheet view in place, it is then possible to begin looking at the motion in the funnel over a period of time, such as a quarter. As buyers progress through their individual buying processes, the transitions in the funnel can be viewed and analyzed, showing where in the funnel there is growth, and where in the funnel there is shrinkage.


If a large number of leads have been passed to sales as Marketing Qualified Leads (MQLs) and accepted as Sales Accepted Leads (SALs), this may be viewed as a very productive quarter, but if the top of the funnel has been neglected and there is a decrease in awareness and a lower number of inquires than normal, this is a warning sign for future funnel trouble.

With the funnel understood in these terms, our ability as marketers to assess the buyers toolkit becomes very valuable as we can understand what resources are contributing to transitions at each stage of the funnel. If there is a gap in funnel motion at a certain stage, and investment in the buyer's toolkit at that stage can be made.

Presenting a marketing funnel in a "balance sheet" and "income statement" view allows marketing to clearly demonstrate their relevance to the business, justify investments in top-of-funnel activities, and make meaningful contributions to revenue forecasting. Whereas approaching marketing analysis from a bottom-up ROI perspective runs into significant challenges as the complexities of the B2B buying cycle come into play, approaching it from a top-down perspective brings clarity and consistency to the task.






As marketing teams begin to present this "balance sheet" and "income statement" view of the marketing funnel, the ability for the business, and the board to objectively understand marketing's contribution increases. With that shift, the well known tenure challenges of today's CMOs and the compensation imbalances between marketing and sales may begin to slowly disappear.

Lead Scoring: Eight Critical Questions to Consider

Much of the conversation around how best to set up lead scoring tends to focus around the aspects of the buyer's digital body language that are most interesting. What whitepaper, excerpt, or download they last looked at, and what this means in terms of their propensity to purchase.

These are all great discussions to have, but there are eight critical questions that need to be contemplated and discussed in order to build a lead scoring algorithm that will truly work in a business environment:

1) What are Your Outputs?: are you using lead scoring to determine who to hand off to sales? what message to communicate to them? who to nurture further? which accounts to get deeper visibility into? all of the above? Understanding your lead scoring outputs first is key in understanding how you want to approach the scoring of leads.

2) How does Time affect your Scores?: it's necessary to think through how the relevance of your prospect actions, and hence their lead score, degrades over time. An action 6, 12, or 18 months ago will likely not have the same relevance as the same action last week. For scoring interest level, this time factor is crucial, whereas for scoring on buyer role, this may not change as rapidly over time.

3) What Dimensions are Critical?: In lead scoring, it is important to clearly define what the question is that you are asking, and to build your scoring algorithm to match that question. If multiple lead scoring dimensions are merged into one, you will likely run into a challenge. Two of the most commonly used scoring dimensions are who the prospect is (explicit data like title, industry, and revenues) and how interested the prospect is (implicit data like web interest, search, and downloads).

4) How do you Cap and Bucket Scores so they are manageable?: When building a lead scoring algorithm, there are often a few buckets of data that come into play. For example in scoring the lead explicitly (who they are), you may look at title, industry, and revenues to determine whether the individual is highly qualified. To do this, it is often best to cap the scores available for each individual bucket. For example, if you are looking at the title to find an executive responsible for content strategy, you may give 10 points for "VP", "Content", "Digital", "Media" or "Production". However, would you want to give 50 points for a "VP of Digital Content and Media Production". Likely not, so this is where caps are needed. 10 points for any of the key terms, up to a maximum of 20.

5) Are your Scores Loosely Mapped to the Ranks that Determine Follow-Up?: If you are going to teach sales to follow up with leads that are defined as "A leads", you need to build in the flexibility to slightly adjust the bar on what makes a lead an "A lead" over time, without retraining sales. The best way to do this is to have both a lead score (a number such as 0-100) and a lead rank (a letter or grade such as A, B, C). Mapping the lead score to the lead rank allows you to adjust your criteria while sales does not change their process.

6) Do you Allow Sales to Cherry-Pick More Leads?: In many environments, especially when lead scoring has been implemented and only good leads are passed to sales, the sales team will feel as though they need more leads. They will ask for the lead funnel to be opened up to them so that they can "Cherry Pick" leads that they deem to be good. Allowing sales to cherry pick has opportunities as well as significant risks, however, and should be discussed carefully upfront.

7) If Sales Does Not Act, do you Claw Back the Lead?: In an ideal world, sales follows up with all leads. However, this is not the reality that most organizations live in, so a process is needed for automatically clawing back the sales lead into marketing if it has not been followed up on in a short time period. Once the lead has been clawed back, it can be re-allocated to another sales person, re-entered into a nurture program, or passed to a partner channel.

8) Have You Provided Sales with Disposition and Nurture Options?: If leads are not being followed up on by sales, it is difficult to adjust your processes unless you know why. Providing sales with options for lead disposition, including automated nurture programs that will continue to educate the lead until it is again ready for sales, can provide both great insight into reasons for lead rejection and foundation for better nurturing of leads.


By thinking through these eight critical factors up front, your lead scoring process will avoid a number of challenges on its road to adoption and success, and will succeed in driving revenue for your organization.

Lead Scoring - Providing Disposition Options

Handing scored and qualified leads to sales in order for them to follow up is an inexact science. Continual optimization of the process is necessary in order to understand what aspects of a buyer’s digital body language are key to understanding buyer’s intentions. One of the best sources of this information is the sales team themselves. However, as any marketer knows, getting information out of a sales team can be challenging. On a topic such as the quality of an individual sales lead, it may in fact seem almost impossible.

Recently, we talked about the need to implement a claw-back system for scored leads that are passed to sales and show no sales activity. This approach is useful, but is a black and white system. Either a lead is good and is worked by sales, or it is not good and is ignored and quickly clawed back. There is no opportunity for middle ground, and no opportunity for feedback from sales.

If, instead, the sales team is presented with disposition options for the lead that feed directly into appropriate lead nurture campaigns, the best of both worlds is achieved. By having an option to pass a lead back to marketing, with a specific disposition that guides what will happen next, the sales person is able to maintain ownership of the lead. However, by carefully constructing the set of disposition options, marketing can learn much more about why the leads were not accepted by sales than they ever would have by asking sales to fill out a feedback form.

For example:
- If a lead is deemed by sales to be slightly too early in their buying process, they might enter the lead into a “Late Stage Buyer Nurturing” lead nurture program that provides case studies and ROI analysis to guide a prospect towards buying

- If a lead is deemed by sales to be too junior to make a buying decision, they might enter the lead into a “Convince Your Executive Team” nurture program that provided key information to make an internal business case for your solution

- If a lead is deemed by sales to be more interested in an alternate product (Product B), they might enter the lead into a “Product B Nurturing” program

These are only a few examples, each organization will have different options. The technique of providing these “lead disposition” options to sales in order to provide sales with a “middle ground” option, while at the same time providing rich insights to your marketing team as to why a lead is being rejected is extremely valuable.

This question is one of 8 critical lead scoring questions to consider when thinking about a lead scoring system.

Cherry Picking of Leads: B2B Marketing to Sales Handoff

Should we allow sales to cherry pick leads that, based on lead scoring, we have deemed not to be ready for sales?

Steve Kellogg at Astadia raised the question very aptly in his Endless Lead Loop post, and it's a question we all face as we wrestle with the business process of lead scoring and handing leads from marketing to sales. Let me start by saying that there is no right answer here, and businesses that have consciously decided to allow cherry picking are not necessarily doing anything wrong.

However, I would make a strong argument for "No."

The better we get at lead scoring, the more factors we are able to consider. We look at multiple dimensions of lead scoring to split the "who" from the "how interested", we look at multiple components of a score and allow each component to only contribute a maximum amount, and we take time into account by degrading lead scores over time. Over time, as we work with sales, we are able to build a fairly accurate picture of what matters to them in a lead.

However, there will always come a time when sales is not getting, in their view, enough volume of leads, and they will ask to open up the funnel so they can "cherry pick" the leads that they deem good. Sounds harmless, as some might turn into opportunities, and those that don't can continue to be nurtured.

It is, unfortunately, not a harmless activity. If we are connecting sales with buyers who are too early in their buying process to be ready to talk to sales, we run a very real risk of alienating those buyers and pushing them away. Despite our good intentions, this cherry picking activity can have significant negative consequences, as prospective buyers who might be good opportunities later can disconnect from an otherwise promising education process early in their buying cycle.

Better than allowing cherry picking, is to keep with the same scoring methodology, but open the funnel slightly. If an A-Lead is passed to sales, and 80-100 points is deemed to be an A-Lead, then keep the same process in place, but open the funnel up so that a A-Lead is now from 60-100 points. By doing this, we prevent sales from negatively impacting early-stage prospective buyers, but still allow them more leads in the funnel.

This question is one of 8 critical lead scoring questions to consider when thinking about a lead scoring system.

National Instruments: Multiple Activities Leading to Multiple Responses

National Instruments has done a great job of creating an information rich web presence that provided relevant and useful information to their audience of scientists and engineers. They had implemented a very elegant equitable exchange of information process that asked for small amounts of information from their audience in exchange for access to the information resources, and were nurturing their prospects based on the information they had requested.

The challenge that Helena Lewis and the team at National Instruments needed to tackle though was what happened in a prospective buyer was very active on their site and accessed multiple information resources in different areas. Here is a case study on how they tackled the challenge, from Digital Body Language:

National Instruments: Multiple Activities Leading to Multiple Responses


National Instruments leveraged the rich information on prospects’ interests that it gleaned from prospect digital body language on its Web site to deliver highly targeted and relevant communications. The success of these communications was evident in the very high open and clickthrough rates discussed earlier. To achieve this, however, National Instruments had to overcome an operational challenge.

The mapping of online activities to communications was straightforward, but also created a challenge. What should happen if a site visitor performs multiple actions that warrant a communication? For instance, downloading four whitepapers should not result in four communications.

To ensure that prospects are not inundated if they perform a number of triggering activities, National Instruments built a waiting period of 24 hours into its scoring. If multiple actions were seen in a 24-hour period, the actions were scored individually and the most relevant communication was selected. Similarly, if an action had been performed before (for example, downloading an automated test guide), the prospect was not sent communications that had this as a call to action.

This solved the challenge of too many communications, but National Instruments also realized that certain key actions should bypass this logic. For example, if a visitor abandons a shopping cart, or saves the configuration of a product, a communication would be immediately triggered. The 24-hour delay was reserved for communications that were deemed less critical.

Since National Instruments is a global organization, each time it learned a better way to interact with customers and built processes for doing so, it replicated that logic and structure and separated it from the content. In this manner, it only needed to translate content and messaging to roll out its program to any of 35 countries.