Survey Suggests Marketers Are Moving from Paid to Social Media

Summary: a new survey suggests that marketers are less focused on lead generation than on final sales, growing current customers and building online communities. I’m not sure I trust the data, but it’s a pretty picture nevertheless.

I don’t know quite what to make of the 2009 Survey on Marketing, Media and Measurement released earlier this month by custom content company King Fish Media.

- On one hand, it’s a rare opportunity to see data from business, rather than consumer, marketers. (Of the 230 respondents, 52% were pure B2B and another 36% were mixed B2B and business-to-consumer.) So I'd really like to believe it.

- But on the other hand, the sample seems dangerously unrepresentative: 44% said their organization’s primary industry was “publishing/media/advertising/marketing”, which is vastly higher than the real-world proportion. Presumably this was the result of the survey method – an online survey based on email invitations to the lists of King Fish and co-sponsors HubSpot, Junta42 and Upshot Institute. In addition to the industry skew, this probably reached a group that’s much more online-oriented than marketers as a whole.

The best I can do is to treat the results very carefully: assuming that this group shares some characteristics of the broader universe, but keeping in mind that some answers might reflect its atypical composition. Here goes.

1. Marketing Measurement Practices

The group reported using three broad types of marketing success measurements:

- 91% measured new customers acquired or leads generated.
- 63% measured customer retention or sales from current customers or lapsed customers.
- 54% measured brand-marketing-style metrics such as awareness, perception or intent.

Directionally, this seems about right: more marketers focus on new business than on existing customers, and brand-style measurements are less common than business results. The figures for existing-customer measurements are higher than I would expect, but perhaps that’s because publishing marketers are more directly responsible for renewals than business marketers in general.

Another oddity was that more people report measuring new customers (77%) than leads (73%). An optimist would treat this as evidence that marketers are adopting an end-to-end vision (as they should) rather than ending their responsibility when a lead is handed over to sales. But think the more likely cause is that marketers in publishing are more likely to sell directly (i.e., without a sales force) than in other industries.

Incidentally, the survey also found that 73% of respondents had guidelines in place to measure marketing success, but just 50% said their company requires a measurement plan as part of its program approval process. Treat this as you wish: is it impressive that 73% have measurement guidelines or frightening that 27% do not? Also bear in mind that 91% were at least using measurement on acquisition programs (some, apparently, without standard guidelines). So I think we can conclude that basic measurement is widespread, although its quality and consistency are questionable.

2. Spending on Acquisition vs. Existing Customers

Media spending by purpose was distributed:

- 56% for new leads
- 33% for retention
- 10% for other

This is interesting because I don’t recall seeing other data showing this split. The actual numbers show much more spending on retention than I would have expected. As with the measurement figures, this probably reflects the business of the survey responders.

3. Media Preferences

The main thrust of the survey was how marketers view different media. Marketers were asked to rate "the most effective way to communicate with customers and prospects", with separate answers for each. Here are the results:

	for prospects/leads	for current customers
corporate Web site	75%	70%
social media	73%	72%
custom content and media	70%	77%
face-to-face events	69%	62%
white papers / e-books	67%	52%
Webcasts and virtual trade shows	64%	51%
e-mail marketing	58%	78%
online advertising	42%	13%
direct mail promotions	33%	34%
print advertising	33%	17%
broadcast advertising	10%	11%

If there’s a pattern here, it’s that awareness-generating media (e-mail, direct mail and online/print/broadcast advertising) rank shockingly low, especially for prospecting. Apart from using email for customer communications, the respondents gave their highest rankings to the corporate Web site, social media, and custom content.

But how, exactly, can they attract traffic for the Web site, social media message and custom content if they don’t reach out to new audiences? I can think of (at least) two answers:

- they can’t, and the answers just reflect an infatuation with online media. I’m not saying the respondents are poor marketers: chances are they really do use the low-ranked media, but don’t consider them terribly effective. (Other answers in the survey suggest the same thing, showing that budgets are moving away from the low-ranking media to the high-ranked categories.)

- they can, by using social media and custom media in the awareness- and traffic-building roles previously handled by paid advertising. Put another way, the traditional first steps of generating awareness and interest are handled by the community rather than by marketers themselves. In this world, marketing’s role becomes to nurture communities of enthusiasts and evangelists, and then to meet the needs of prospects attracted by the community. This is what I meant in my September 23 post about community-centric marketing replacing customer centricity. (Can I coin CBM as a new acronym for Community Based Marketing?)

Obviously the second possibility is more intriguing. It’s surely correct to some degree, although the Big Question is how quickly and how far marketers’ role will shift. Given my concerns about this survey, I wouldn’t treat its results as definitive answers. But they're still tasty food for thoughts.

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SalesFusion Combines Online and Offline Marketing with CRM

Summary: SalesFusion combines all channels within marketing, and merges marketing automation with CRM as well. This one-stop-shopping will be most attractive to small and mid-size companies, although I expect that larger firms will eventually want it too.

Look, I know online marketing is important. But let’s not forget that offline channels still account for nearly 90% of total advertising expenditures. Business marketers probably spend more online, but, once you add in the cost of salespeople, I’d guess that online spending still accounts for less than 10% of the combined total.

My point here – have you met my pet, Peeve? – is that nobody needs a comprehensive online marketing suite. They need a comprehensive marketing suite, period, that includes both online and offline activities. And, while we’re on the subject, they need REALLY TIGHT integration between marketing and sales automation, if not one shared system.

This brings us, somewhat abruptly, to SalesFusion360, a B2B marketing automation system that does merge online, offline and sales channels. This breadth isn’t accompanied by tremendous depth: SalesFusion’s campaign management and built-in CRM tools are a bit limited. But the system does offer a comprehensive solution for smaller firms and, at least on the CRM side, can integrate with more powerful solutions including Salesforce.com, Microsoft Dynamics CRM and Siebel CRM On Demand.

Let’s start with SalesFusion’s strongest point, which is the scope of marketing channels supported. Beyond the usual outbound email and Web forms, the system provides:

- Web analytics to support search engine optimization and Web advertising,
- API-level integration with Google AdWords to support paid keyword campaigns,
- IP-address lookup to identify the company and location of anonymous Web visitors (and send rule-based alerts to salespeople),
- personalized URLs (PURLs) to tie in responses from offline campaigns.
- online chat and
- telemarketing support through the CRM component.

Results from all these channels are managed through a unified campaign structure, which creates a hierarchy of campaigns and subcampaigns to allow channel-level rollups. Campaign data includes budgets, actual costs, and revenues imported from sales opportunities.

The email features cover all the basic requirements: template-driven personalized messages, universal and campaign-level exclusion rules, and both static and dynamic list definitions. Campaigns can be executed manually by the user or triggered by selected events including completion of a form, selecting a specific answer within a form, completing a step in a multi-step marketing campaign, or reaching a score threshold.

The main weakness is that multi-step campaigns can only send messages in a fixed sequence (i.e., no branching based on prospect behavior) at fixed intervals. A skilled user could implement some branching by using step-level inclusion and exclusion rules to send different messages to different people and by using Web forms to send leads to new campaigns. But these are awkward solutions. SalesFusion promises a more flexible, visual campaign builder and dynamic content generation for delivery early next year.

The system’s features for lead scoring and routing are more impressive. Users can build separate scoring rules for different marketing campaigns, regions, products or other entities. These scoring rules can be active for specified date ranges and can post scores at contact or account levels.

Users can define value ranges (hot, warm, cold, etc.) for each score, and can set up routing rules triggered by entry into each range. These rules trigger an email campaign, send an alert, create a log entry, or add a lead, task or opportunity record in the CRM system. Multiple scores are particularly important at large companies where contacts need to be treated differently for different products, regions and other variables.

Each scoring rule can incorporate Web activity, campaign events, form responses and static data. Score calculations can ignore events before a specified period, but do not make interim reductions as events reach this limit. The system can cap the number of points earned by any one type of event, although this takes some configuration by the vendor. Users can specify whether scores are recalculated on daily, weekly or monthly.

The integrated CRM system provides most of the features needed by small and mid-size companies, and is used by about half of SalesFusion's current clients. The company plans to enhance the CRM system to be more competitive with enterprise-class systems by early next year. The CRM and marketing automation components of the system already work on a shared data structure. Clients who use a separate CRM system can synchronize data via regular updates.

Reporting includes prebuilt dashboards and an ad hoc report writer that lets users query system tables directly. The latter is an unusual feature for Software-as-a-Service systems like SalesFusion, since most vendors are concerned that ad hoc queries could harm system performance.

SalesFusion starts at $250 per month for a light version with limited features, under 1,000 names in the database, five users, and 10,000 emails per month. The lowest-priced full version costs $1,500 per month and includes up to 25,000 names, 75 users, and 125,000 monthly emails. CRM is currently included at no extra cost, although the vendor plans to start charging around $10 per user per month when the enhanced version is released.

The first version of SalesFusion was released in 2003, when the company was named FirstReef. It merged in 2007 with online forms vendor AxiomFire and assumed its current name in January 2009. The system has about 50 current installations, many sold by resellers including some major accounts in Australia and South America. SalesFusion is now expanding its direct sales efforts.

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5 Steps to Marketing Measurement Maturity

Summary: marketing performance measurement can start with simple response tracking, and grow in stages to show business impact, track the buying process, optimize results and demonstrate strategic alignment. Each stage adds new data, systems, measures and processes.

I’ll be talking about marketing measurement this Tuesday at Silverpop’s B2B Marketing University seminar in Palo Alto, with a repeat performance in Boston on November 4. The core of my presentation will be a 5-step measurement maturity model for B2B marketers. This post will give you a brief summary.

A little background: marketers’ objectives for performance measurement generally fall into five broad categories: measure response, show business impact, track the buying process, optimize results and demonstrate marketing alignment with business strategy. Each category has different requirements for data, systems, measures, and processes. Because some of these requirements overlap, there’s a natural progression starting with the simplest requirements and adding new requirements for each stage. This progression leads to a maturity model. Here are the details.

1. Measure Response. The most basic requirement is simply to count the number of responses to each marketing program. This stage also includes the closely related step of calculating the cost of those responses for a simple cost-per-response measure that can be used for a rough ranking of investments.

Key data needs for this stage include mechanisms to capture responses and campaign costs and to link responses to campaigns. This requires a campaign management system to execute the campaigns and track their costs, and a marketing database that stores the identity, promotion history and response history of leads generated by the campaigns.

2. Show Business Impact of Marketing Campaigns. The cost per response tells little about the business impact of a marketing program. You must also know the value of those responses. At a minimum, this requires linking marketing leads to closed sales. This typically means importing closed opportunity records from a sales automation system and linking those opportunities back to the original marketing lead. Add the cost data already gathered in stage 1 (response measurement) and you can calculate a simple Return on Investment based on revenue / acquisition cost.

Of course, true ROI is based on profits, not revenue, and incorporates all incremental costs, not just the initial marketing expense. A proper business impact measurement thus requires capturing the full marketing, sales and product costs associated with new leads, as well as their actual or estimated long-term value. These give a ROI measure that comes reasonably close to showing the true business impact of each acquisition campaign.

In terms of new requirements, this step adds sales opportunity data, which implies integration with a sales force automation or CRM system. It also requires processes to assign opportunities to leads and leads to campaigns, and, optionally, ways to import and connect lifetime costs and revenues.

Keep in mind that this approach only applies to lead acquisition campaigns, not to campaigns that nurture existing leads or customers, or branding campaigns that don’t generate a direct response. This is a smaller issue for B2B marketers than many consumer marketers, who often have no direct way to identify the customers acquired or influenced by their activities.

3. Understand the Buying Process. This stage looks at the impact of non-acquisition marketing treatments on moving customers through the buying process. It requires defining stages within the buying process, tracking the movement of individual leads through those stages over time, recording the marketing treatments applied to those individuals, and measuring the correlation (if any) of treatments to stage changes. The result is both a more detailed understanding of the buying process and a way to decide which treatments are most valuable.

Meeting these requirements implies capturing more information about leads, including static attributes (company, job title, etc.) and behaviors such as Web site visits and email responses. These can be used in scoring models or other tools that decide which stage a lead is in at any given moment. The system must also keep a history of each lead’s stages over time, so it can correlate stage changes with treatments. The treatments themselves are already captured in the marketing database needed for response measurement, so they do not represent a new requirement.

4. Optimize Results. Once you’re tracking lead movement through process stages and measuring the impact of individual treatments, you’re ready to build an end-to-end model that calculates the impact of each small change on final sales. You can then optimize the combination of treatments across the process. For example, you might find you can spend less on acquiring new leads if you spend more on nurturing existing ones, to produce the same sales volume at lower cost.

The calculations for this type of optimization are fairly simple, and they don’t require any new information beyond the previous stage in the maturity model. But you do need more precise information about the impact of different treatments, which means formal testing of alternative treatments and careful analysis of results. You’ll also need a business simulation model that can estimate the impact of changes on near-term revenues and costs, since the company still has its quarterly targets to hit. You'll also need to define you goals -- higher revenue? higher profit rate? lower marketing costs? -- so you know what to optimize.

Ideally, you’ll also add optimization software that can automatically find the best of all possible treatment combinations. But few B2B marketers have the data volume or statistical skills required for this, so you’ll probably end up manually running a variety of scenarios through your simulation model instead.

5. Demonstrate Strategic Alignment. Delivering the optimal set of treatments won’t satisfy your CEO if your marketing programs don’t align with the larger business strategy. That alignment may in fact require campaigns that produce low short-term returns, such as investing in a new product or market segment.

To demonstrate alignment, you must first show that your planned marketing activities support business goals, and then show that those activities have yielded the expected results. For example, a strategy based on selling to a new group of customers might yield a marketing plan with 10% of acquisition spending aimed at generating leads from that segment, and a goal of that segment accounting for 5% of new leads received.

The exact requirements for this stage will depend on your specific strategic goals. But it’s likely that you’ll need more information about the purposes of your marketing spending (so you can show which funds are supporting which strategic goals) and more about lead attributes and behaviors (so you can show that results are in line with expectations).

Incidentally, demonstrating strategic alignment doesn’t depend directly understanding the buying process (stage 3) or optimizing results (stage 4). So a company that has reached stage 2 in the maturity model could jump immediately to demonstrating strategic alignment if desired.

Final Thought: once you get past counting response, all later stages in the maturity model assume you are measuring your marketing performance against the ultimate goals of closed sales and long-term customer value. This is increasingly necessary as marketing remains involved with leads even after they are officially transferred to sales. It implies that marketing and sales must integrate their systems, so they can view, coordinate, analyze and ultimately optimize sales and marketing activities across the entire buying cycle.

In companies where the marketing's responsibility still ends with the hand-off of qualified leads to sales, the maturity model could be adjusted to optimize only through that stage. But that's an increasingly obsolete approach.

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Beautiful BABI: SiSense PrismCubed Offers Business Intelligence for Business Analysts

Summary: SiSense PrismCubed offers a reasonable option for a business-analyst business intelligence system. It’s probably a little harder to use than some competitors, but gives a bit more power and flexibility in return.

SiSense PrismCubed, officially launched this past August, is another member of the growing set of business intelligence systems aimed at empowering business analysts to build their own applications. I’ve also written about QlikView and Lyza, and think there are others.

What distinguishes these tools from other business intelligence systems is they let non-technical users manipulate source data in more sophisticated ways than a spreadsheet or report writer. Specifically, data from several sources can be merged on a common key, filtered, aggregated and processed through complex formulas.

This sort of manipulation has traditionally required SQL programmers, OLAP cube designers, or similar technical experts. Allowing business analysts to do it without having to learn deep technical skills is precisely what lets them build applications with minimal external assistance. (I say "minimal" because technical staff must still handle connections to the source data.)

These systems also provide report creation and distribution. But unlike business-analyst data manipulation, those capabilities are also found in other business intelligence products.

You’ll note that my definition does NOT specify a particular database technology, such as in-memory or columnar, that the data is updated in real time, that the system is targeted at mid-sized businesses, or that results are distributed pervasively through the organization. Those have all been proposed as ways to classify business intelligence systems, and several of the products in my business-analyst business intelligence (BABI--how cute!) category fall into one or another such group. But I think it’s a mistake to focus on those other features because they don’t get at real value provided by these tools, which is the flowering of applications made possible when business analysts can create them independently.

Now that I've defined a new type of application, complete with the all-important acronym, the next step is defining an evaluation framework to help compare the competitors. I’d like to claim I do this through deep research and brilliant insights into user needs, but, in fact, I generally start with the features in the existing systems. This runs the risk of missing some critical requirement that no vendor has yet uncovered, but it saves a ton of work. And I can still argue that I’m piggybacking on the vendors’ own deep research and insights as embodied in their products.

In any event, a starter set of review criteria for BABI systems (sorry, but I find the acronym irresistible) would include:

- combine data from multiple, heterogeneous sources (relational databases, CSV files, Excel tables, etc.)

- allow non-technical users to define processing flows to manipulate the data (merge, filter, aggregate, calculate)

- present the manipulated data in a structure that’s suitable for reporting and visualization

- allow non-technical users to create applications including reports, visualizations, and (optionally) additional functions such as data refresh and export

- allow other users to view (and optionally interact with) the applications

- meet reasonable performance standards for data load, storage, response time and scalability

- use appropriate technology (actually, I don’t care if the thing is powered by hamsters. But understanding the underlying technology helps to predict where problems might arise.)

- affordable pricing (not exactly a criterion, but important nevertheless)

Obviously these criteria could be much more detailed, and no doubt they will grow over time. But for now, they provide a useful way to look at PrismCubed.

1. Combine data from multiple sources: PrismCubed provides a wizard to connect with different data sources, including SQL Server, Oracle, CSV files, Excel and Amazon S3 logs (which earns them extra coolness points). The system can read the database schemas directly, saving users the need to define basic data structures. Users have the option modify structures if they desire. A connection can be live (i.e., the source is requeried each time a report is run) or reloaded on demand from within a completed application. This provides real-time data access, which isn’t always available in business intelligence systems. The system can also reload data automatically on a user-specified schedule.

2. Allow non-technical users to manipulate source data: PrismCubed does a particularly good job here. At a basic level, users can write complex formulas to add derived fields to a table during the import process. More important, a drag-and-drop interface lets them build complex visual processing flows from standard icons including data definition, filtering, inclusion or exclusion, unions, and top or bottom selects. These flows can combine multiple data sources and include branches that generate separate output sets that are all available to use in applications.

3. Present the manipulated data for reporting: the system automatically classifies input data as dimensions (text, dates, etc.) and measures (numbers which can be aggregated). Users can override the system’s assignments and can add new dimension fields during the data load. They can create derived measures at any time. Once the load is complete, the system presents the dimensions and measures in an “ElastiCube” available for reports and other applications.

4. Create reports and other applications: the system provides a remarkably rich development environment. Users build applications by dropping different types of objects (which the vendor calls widgets) onto dashboard pages. Widgets can make selections; display data in pivot tables, charts, calendars, and images; and execute actions including refresh data, jump to different pages, query external data sources, edit data, and export to Excel. A dashboard can have multiple pages.

The primary reporting widget is the pivot table, which itself is built by dragging dimensions into rows and columns, and the measures into cell values. Users can apply filters to widgets, such as selecting the top 10 values for a dimension. These filters can be static (a fixed list) or dynamic (reselected each time the dashboard is updated). PrismCubed also provides special features for time series calculations such as period-to-period growth and differences. That's a nice touch, because those can be quite difficult to define with conventional reporting systems.

Reporting widgets can be connected to the ElastiCube dimensions and measures or directly to SQL data sources. Users can also specify whether selections made in one widget affect the data displayed in other widgets. There are actually three options here, including complete independence, direct links from one widget to another, and global impact on other widgets. This gives more flexibility than systems that automatically apply global selections, but does force users to do more work in specifying which approach they want.

Widgets, filters and other components can be stored in a central repository and reused across applications.

5. Share applications: Users can export dashboard contents to Excel tables or can copy an entire dashboard as a static PDF. Applications, including underlying ElastiCubes, can be copied and run on another user’s PC. In addition, a Web server due for release this month (October) will let dashboard creators publish their dashboards to a central server, where other users will be able to access and modify them. The server will provide fine-grained control over what different users are allowed to change.

6. Scalability and Performance: SiSense has tested the PrismCubed engine on multiple terabytes of data. It cited one client who loaded 30 million telephone call detail records in 30 to 90 minutes. Loaded data usually takes somewhat less disk space than the original source. The system currently requires a complete reload to add new data to an existing ElastiCube, although the vendor plans to add incremental appends by the end of November. Once the data is loaded, reports within applications usually update in seconds.

7. Technology: PrismCubed stores data in a columnar data structure. It also stores a dimension map for each column, but doesn’t preaggregate the data along the dimensions. As with other columnar databases, this avoids the need for specialized data structures to handle particular queries. When data has not been preloaded into the system, PrismCubed can also run the same query across multiple external data sources.

Although PrismCubed stores the entire ElastiCube on disk, it only loads into memory the columns required for a particular query. This lets it can handle larger data sets than purely in-memory systems without massive hardware. There might be some problems if the selected columns for a query exceeded the system’s available memory.

PrismCubed runs on Windows PCs with the .NET framework installed. On 64 bit systems, this means the amount of potential memory is virtually unlimited. Although PrismCubed itself is new, a previous version of the product using the ElastiCube database engine was launched in September 2008 and has more than 6,000 users.

8. Pricing: PrismCubed is priced on an annual subscription basis, which is unusual for this type of product but common among hosted BI vendors. SisSense offers several versions of PrismCubed, ranging from a free Viewer that can only access dashboards created elsewhere, to a $1,500 per year Professional edition that allows full creation of dashboards and ElastiCubes. There are also a free version (limited to 2,000 rows of data), a $300 per year Personal edition (which can create dashboards but not share them), and a $700 per year Analyzer that can build and share dashboards but not ElastiCubes. Server pricing wasn’t quite set when I spoke with SiSense but will probably be around $3,500 per year per server.

These prices are quite reasonable compared with similar vendors, even considering the recurring annual subscription fees, particularly because the end-user Viewer is free. Price details are published on the vendor’s Web site.

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Survey Looks for Hostility to Behavioral Targeting, and Finds It

Summary: a new survey found that most Americans oppose behavior-based Web targeting. The authors clearly had an agenda, but the industry still needs to present its side of the story.

A recent survey conducted by professors by UC/Berkeley and University of Pennsylvania concluded (to quote its full title) that “Contrary to what marketers say, Americans Reject Tailored Advertising and Three Activities That Enable It.” Is it just me, or do I detect a bit of hostility?

The headlined finding of the survey was that 66% of respondents said they did not want Web sites to show ads tailored to their interests. As eMarketer pointed out in its article on the study, this conflicts with other surveys have found consumers receptive to targeted Web ads.

The Berkeley/UPenn study claims it is more accurate because it is the first nationally representative telephone (rather than Internet-based) survey on the topic. I doubt that really had much impact on the results. As a detailed critique by the business-friendly Progress & Freedom Foundation points out, the answers were more likely influenced by the structure of the poll itself, which asked a variety of somewhat tendentious questions leading up to the final answers.

My own critique is that the questions all asked whether people wanted to see tailored ads, not whether they preferred tailored ads vs. non-tailored ads. People may have interpreted the unstated alternative as no advertising at all. In that case, their rejection had less to do with tailoring in particular than with the near-universal dislike of advertising in general.

Still, the answers I found most interesting have received relatively little attention. This was a set of three questions that found:

- 67% of Internet users agree they have “lost all control over how personal information is collected and used by companies”, but

- 58% feel “most businesses handle the personal information they collect about consumers in a proper and confidential way” and

- 54% agree that “existing laws and organizational practices provide a reasonable level of protection for consumer privacy today”.

In other words, people have finally accepted Scott McNealy’s famous advice from 1999: “You have zero privacy anyway. Get over it”.

I’d like to end the story there, if only for artistic reasons. But the survey also asked several questions about consumers’ understanding of current privacy laws, which basically found that most people think they have more protection than they really do. Another series of questions found support for laws giving consumers rights to insist that companies delete their information.

I don’t take the results too seriously because the questions didn’t indicate these would be new laws or balance the laws against reduced free content or the cost of more regulation. But they do suggest that people might support stronger regulation if they understood how poorly they are now protected. So there continues to be a real need for marketers to both do a good job of protecting consumer privacy and of educating the public and legislators about the benefits provided by easy access to consumer information.

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