0 How Raab Associates Converted to ZohoCRM In One Weekend: a B2B CRM Success Story

Raab Associates is really two businesses: the technology consulting practice run by Yours Truly, and a marketing agency specializing in children’s books run by my beautiful and brilliant wife Susan. We keep them largely separate, but I am inevitably involved in her technology decisions. So when her ancient Goldmine CRM system finally crashed last week, we both scrambled to pick a replacement.

From my usual lofty perch in enterprise software world, Susan's requirements seem stick-figure simple: accounts, contacts, opportunities, lists, and mass emails. So our first thought was to find a system that offered those plus some cool new things like social media profiling. But a quick scan of the market showed that none of the neat new systems also offered the basic functions with with enough refinement and flexibility to meet Susan's needs.

This pushed us back to the more standard CRM options.  To my dismay, we found ourselves ruling out one after another for various. I even briefly suggested we reconsider Goldmine, an thought that was quickly rejected.  Eventually we took an unhopeful look at ZohoCRM, which I know as a popular small business system but had never considered particularly advanced. Happily, the system has a very thorough online user manual, so I was able to check it out in detail.

Even more happily, the answers all came back positive as I imagined working through Susan’s basic business processes in Zoho. Build contact lists, check. Mass emails, check. Opportunities linked to campaigns, check. Pull-down status list and callback date on opportunities, check. Custom filters across all field types, check. End-user report writer, check. Multi-field search, check. A bunch of other details that I no longer recall, check check check. Reasonable cost, double check: we would have grudgingly paid a couple hundred dollars a month for a solution, but Zoho’s mid-tier Professional edition costs all of $20 per month with no limits on database size (Susan has about 14,000 contact records – well above the minimum for many small business systems). We may even splurge for $35 per month enterprise edition, which provides some advanced automation features but is probably overkill for most small businesses.  Just call me Diamond Jim.

At this point, we were ready to sign up for the free trial account, which was a simple process and didn’t ask for a credit card. Let me point out that I purposely hadn’t signed up sooner because I didn’t want to waste time exploring a system that I wasn’t pretty confident would meet my needs. Diving in too soon is a classic mistake among software buyers – and, in this instance at least, I actually followed my own advice.  (While I'm patting myself on the back, I'll also point out that we evaluated the software against our actual business process, not an arbitrary feature checklist.  That's another best practice that too few buyers follow.)

We now pulled a small set of test records from Goldmine to test the import function. The online manual guided me through the exact steps necessary, complete with a handy checklist of preparatory tasks.  When I went to load the file itself, I got the first of many delightful surprises: Zoho took a guess at mapping the input fields, based on their names, and got about half right. That’s a pretty sophisticated function and a big time-saver. It’s the sort of refinement you don’t see in a new system because it’s not essential to get the product into market, but gets added after enough users request it and the developers have some breathing room. Zoho has actually been around since 1996 (although CRM came later), so they’ve had time to add a lot of those little helpers.

In any event, the test import worked perfectly the first time out, which was a great feeling of accomplishment. Susan and I played with the system a bit more now that we had some real data in it, and found all sorts of nice little options, like being able to rename objects (she calls an opportunity a “pending record”), rearrange the fields on each screen, change the order of sections, and move fields from one section to another.  Again, none of these is cutting edge, but they’re not always available and make a big difference in making the system more usable.  The interface itself was also highly intuitive – lots of nice dragging to move the fields around, for example. There were plenty of other unexpected goodies that I would have otherwise needed to configure or live without, like automatically listing the associated contacts when you view an account record, and listing the associated opportunities – I mean, pending records – when you look at a contact. And, oh yes, you can control which fields are displayed on those related records.

At this point we were feeling pretty good about actually pulling off the conversion, so I spent all day Sunday manually cleansing those 14,000 contact records to ensure the critical data was populated. Even Zoho couldn’t help with that one. I finished around midnight and had a moment of panic when I saw that Zoho would only import 5,000 records at a time.  But it turned out to accept all three batches without waiting for the first batch to finish, so I was able to submit them and get some sleep.

I woke up bright and early (well, actually, late and cranky), feeling pleased that Susan could start using the system without missing a business day.  Alas, we found that somehow there were twice as many account records as expected. A quick call to Zoho support pointed us to a rollback function that should have cleaned up the problem in a few seconds. Sadly, it rolled back one set of records but not the other (remember, there had only been one import).  I spoke again with Zoho support, who promised to look into it but hadn’t accomplished anything several hours later.  At that point, I realized – duh – that it would take about two minutes to delete the records manually (you can only delete 100 at a time, but it’s three keystrokes for each batch, so you can probably do about 50 batches per minute). Once I figured that out, I cleaned out the old records and reimported everything, and we had a clean set of data.

Susan has been working with the system for the past two days, and I’ve been peeking over her shoulder and poking around a bit myself.  ZohoCRM is certainly not perfect – there are bunch of little things she would like to do, such as preview a template-based email with the variables populated. There are also some oddities like two unrelated sets of email templates, a vestige of Zoho's earlier separate systems for CRM and mass mailings. Those quirks take a bit of getting used to but are far from show-stoppers. There are some other tasks that cumbersome at the moment, but I suspect we’ll be able to automate once we have time to explore those functions. And, yes, there are some things it doesn’t do that Susan would like, such as associating multiple email addresses with the same contact. I wouldn’t exactly say they’re trivial – certainly not to Susan – but she can live with them.

We're generally satisfied with customer support: phone calls aren’t always answered immediately, but after about a minute on hold, a very nice lady picks up the line and offers to take a message. I appreciate the human touch, and, more important, the opportunity to get immediate help if something is truly urgent. We do get callbacks in an hour or two and the agents have been pleasant and helpful, which is about all I can ask. There’s a “how’d we do?” email after each interaction, which is a good sign that Zoho is trying to do a good job.

Bottom line: We’re still in the honeymoon period, so I may find Zoho isn’t really as great as I think.  On the other hand, I proposed to Susan almost immediately after meeting her and that's worked out just fine.  So I'd say ZohoCRM is worth a close look for small business CRM, even for people who think it may be too simple for their needs.

0 How to Get the Most from Social and Behavioral Data: Webinar, March 19

Raab Associates has been gradually relocating from New York to Pennsylvania over the past two weeks. I won’t subject you to a post like “what B2B marketers can learn from moving companies”, which is one of my least favorite ploys for repackaging old advice in a “fun” format. In fact, I only mention it to explain why I haven’t been writing with my usual frequency and why this post is relatively brief.

Still, I did want to let you know that I’ll be giving a Webinar next Tuesday, March 19 at 2 p.m. Eastern on “Making the Most of Social and Behavioral Data for B2B Marketing”. It’s sponsored by Mintigo, a hard-to-classify vendor with technology to scan the Web for prospects and predict their interests. You can register here.

The chaos of moving has slowed down my slide preparations, which are made even harder by the fact that our 100-year-old house has such uneven floors that my chair keeps rolling away frrrrom mmmy desssssk. But I did finish my research before they packed up our computers, so the content itself will be solid. Without giving away all the goodies, some of the more interesting things we’ll cover include:

- where social and behavioral data are used in the marketing process. This actually matters quite a bit: there are some things that social and behavioral sources can provide, and others they can’t. You have to be sure you’re using them correctly and supplementing with other sources where appropriate.

- what to do once you capture the data. Traditional marketing data was pretty easy to manage because there wasn’t that much of it.  With social and behavioral, you’re surfing a flood. We’ll talk about how to keep your head above water.

- how to deal with the ephemeral nature of much social and behavioral data: without belaboring the flood analogy, conditions change rapidly and marketers must react quickly. We'll discuss what this means and how to do it.

- which data elements are available from different sources.  It isn’t news that each social network works differently, but it’s still eye-opening to see just how distinct they are. We'll talk about which network is best for different purposes.

- what all this looks like from a sales person’s viewpoint. Most marketers will try to swim in this data despite the rough surf. Sales people are more likely to leave the water and have a hot dog. We’ll talk about ways to keep them immersed.

I’m more curious than anyone to see my final slides, but have no doubt that the session will be useful and interesting. It’s an important topic: join me if you can.

0 Moving On: Lessons from the B2B Marketing Trenches

 
I’ve just ended my six month tour as VP Optimization at LeftBrain DGA, and am now returning full time to my usual consulting, writing, and general shenanigans. It was fun to work again as a hands-on marketer. Here are some insights based on the experience.

- lots of content. We all know that content is king, but sometimes forget the king has a voracious appetite. A serious demand generation program might move contacts through half dozen stages with several levels within each stage and several messages within each level. This could easily come to forty or fifty messages, each offering a different downloadable asset.  The numbers go even higher when you start to create separate streams for different personas. Building these materials is major undertaking, first to understand what’s appropriate and then to create it. But deploying the initial content is just the start: you then have to monitor performance, test alternatives, and periodically refresh the whole stream. Finding efficient ways to do this is critical to keeping costs and schedules within reason. (Note that I’m talking here about email programs to nurture known contacts, not acquisition programs to attract new names. That takes another massive content collection.)

- content isn’t everything. It’s an old saw among direct marketers that the list determines most of your response rate and the offer controls for most of the rest.  Actual creative execution (copy, graphics, format, etc.) accounts for maybe 10% of the result. We proved this repeatedly with tests that used the different content at the same stage in the campaign flow: basically, results were similar even with content originally designed for different purposes. Conversely, the same piece of content had hugely different results at different places in the flow. What this meant in both cases was that response was primarily driven by the people at each stage, not by the specifics of the materials presented.

- simplicity helps. That results are primarily driven by audience doesn’t mean that content doesn’t matter. We did a fascinating (to me, at least) analysis of 100 emails, logging specific features such as number of words and readability scores and then comparing these against open, click-through, and form submit rates. A clear pattern emerged: simpler emails (shorter, fewer graphics, easier to read) performed better. In fact, the pattern was so clear that there's a danger of over-reaction: at some point, a message can be too short to be effective (think of the mayor in The Simpsons, who just repeats “Vote for Me”). So the real trick is to find an optimal length, and even then to recognize that some messages truly need to be longer than others.

- simplicity isn’t everything, either. We did a lot of testing – it was my favorite part of my job – but the content tests were often inconclusive: sometimes shorter won, sometimes longer won, most often the difference was too small to matter. Given that we were starting with competently-created materials, that’s not too surprising. On the other hand, we consistently found that forms with fewer questions yielded better results, typically by a ratio of 3:1. This is one example of a non-content item with major impact; another was contact frequency (more is better, but, as with simplicity, only up to a point). There were other aspects of program structure that I would have tested had time and resources permitted; the goal was to focus on variables with the potential for a substantial impact on over-all results. This generally meant moving beyond individual content tests to items with larger and more global impact.

- test themes, not details. Don’t misinterpret that last sentence: I’m not against content tests. What I'm against is tests that only teach one small, random lesson, such as whether subject line A is better than subject line B. The way to build more powerful tests is to build them around a hypothesis and then try several simultaneous changes that support or refute that hypothesis. (I’ve shamelessly stolen this insight from Marketing Experiments, whose methodology I hugely admire and highly recommend.) So, if you think simplicity is an issue, create one test with shorter subject line and less copy and fewer graphics and a simpler call to action, and run that against your control. This is exactly the opposite of conventional testing advice of changing just one thing at a time.  That approach made sense back in the days of direct mail when you were running a handful of versions per year, but isn’t an option in the content-intensive environment of modern online marketing. And even if you had the resources to run a gazillion separate tests, you’d still need to see larger patterns to guide your future content creation.

- multivariate tests work. As if the infinite number of potential tests were not enough of a challenge, most B2B marketers also have relatively small program quantities to work with. We multiplied our test volume by applying multivariate test designs, which let us use the same contacts in several different test cells simultaneously. This probably needs a post of its own, but here's a quick example: Let’s say you need 10,000 names per test cell and have 20,000 names total. Traditionally, you could just run one test comparing two choices. But with a multivariate design, you’d create four cells of 5,000 each. Cells 1 and 2 would get the first version of the first test, while cells 3 and 4 would get the second version. But – and here’s the magic – cells 1 and 3 would also get the first version of the second test, while cells 2 and 4 would get the second version of the second test. Thus, each test gets the required 10,000 names, but you can still see the impact of each test separately. (Here’s a random article that seems to do a good job of explaining this more fully.). We generally limited ourselves to two or three tests at a time. More complicated structures are possible but I was always concerned about keeping execution relatively simple since we were doing all our splitting manually.

- metrics matter. As it happens, most of the programs we executed rely heavily on form submissions to move people to the next stage. This meant that form fills were the key success metric, not opens or click-throughs. Although these generally correlate with each other, the relationship is weaker than you might expect.  Some exceptions were due to obvious factors such as differences in form length, but the reasons for others were unknown.  (I often suspected but could never prove reporting or data capture issues.)  Of course, most email marketers are used to looking at open and click rates, so it took some gentle reminding to keep everyone focused on the form fill statistics. The good news is we prevented some pretty serious mistakes by using the right measure.  Note that form fills are especially important in acquisition programs responders are lost altogether if don't complete a form that let you add them to your database.

- test results need selling. As you’ve probably guessed by now, I spent much of time lovingly crafting our tests and analyzing the results. But others were not so engaged: more than once, I was asked what we found in a test whose results I had published weeks before. This wasn’t a complete surprise, since other people had many other items on their mind. But we did eventually conclude that simply publishing the results was not enough, and started to go through the results in person during weekly and monthly status meetings. We also found that reviewing individual results was not enough; when we found larger patterns worth reporting, we had to present them explicitly as well. Again, there’s no surprise in this, but it does bear directly on expectations that managers will find important data if reporting systems simply make it available. Most will not: the systems have to go beyond reporting to highlight what’s new, what it means, why it matters, and what to do next. Although some parts of that analysis can be automated, most of it still relies on skilled human effort.

- reports need context. Reporting was another of my responsibilities, and we made great strides in delivering clearer and more actionable data to our clients. One of the things I already knew but was reminded really matters was the importance of putting data in context. It wasn’t enough just to show cumulative quantities or conversion statistics; we needed to compare this data with previous results, targets, and other programs to give a sense of what it meant. To take one example, we reported the winner of a series of email package tests, without realizing until late in the analysis that the response rate for the test as a whole was much lower than previous results. This was a more important issue that the tests themselves. We had other instances where entire waves were missing from reports; we only uncovered this because someone noticed they were missing – whereas, a proper comparison against plan would have highlighted it automatically. Again, such comparisons are widely acknowledged as a best practice: my point here is they have immediate practical value, so they shouldn't just be relegated to the list of “nice but not necessary” things that no one ever quite gets around to doing.

- survival is more important than conversion. That phrase has a vaguely religious ring to it, and I suppose it’s also true in a theological sense. But right now I’m talking about reporting of survival rates (how many people who enter a nurture program actually end up as customers) vs. conversion rates (how many people move from one program stage to the next). Marketers tend to focus on conversion rates, and of course it’s true that the survival rate is mathematically the product of the individual conversion rates. But we repeatedly saw changes in program structure or even individual treatments that caused large swings in a single conversion rate, which was often balanced by opposite changes in the following stage. Looking at conversion rates in isolation, it was hard to see those patterns.  This was an even bigger problem when each rates was calculated cumulatively, so the impact of a specific change was masked by being merged into a larger average. More important, even when there was an obviously related change in two successive rates, the net combined impact wasn’t self-evident. This is where survival rates come in, since they directly report the cumulative result of all preceding stages. Of course, conversion rates and survival rates are both useful: I'm arguing you need to report them both, not just conversion rates alone.

- throughput matters. Survival and conversion rates show the shape of the funnel, but not the dimension of time. We did report how long it took contacts to move through our programs – in fact, a sophisticated and detailed approach was in place before I arrived – but the information was largely ignored. That was a pity, because it contained some important insights about contact behaviors, opportunities for improvement, and results of particular tests. A greater focus on comparing expected vs. actual results would have helped, since calculating the expectations would have probably required a closer focus on how long it took leads to move through the funnel.

- acceleration is hard. A greater focus on timing would have also forced a harder look at the fundamental premise of many B2B campaigns, which is that they can speed movement of prospects through the sales funnel. The more I think about this, the more doubts I have: B2B purchases move according to their own internal rhythms, driven by things like budget cycles, contract expirations, and management changes. Nurture programs can educate potential buyers and build a favorable attitude towards the seller, thereby increasing the likelihood of making a sale once the buyer is ready. They can also track, through lead scoring, when a buyer seems ready to act and is thus ripe for contact by sales. That’s all good and valuable and should more than justify the nurture program’s existence. But expectations of acceleration are dangerous because they may not be met, and could unfairly make a successful program look like a failure.

- drip needs attention.  Like that leaky faucet you never quite get around to fixing, drip programs often don't get the attention they deserve.  In practice, the vast majority of people who enter a nurture program will not move quickly to the purchase stage; most will stall somewhere along the way. This is where the drip program must work hard to keep them engaged. Again, every marketer knows this, but it’s easy to focus attention on the fascinating and complicated stage progressions (remember all that content?) and relegate the drip campaigns to a simple newsletter. Big mistake. Put as much effort into segmenting your drip communications and encouraging response as you put into stage conversions. If you want a practical reason for this, look at your mail quantities: chances are, you’re actually sending more drip emails than all your active stages combined.

- proving value is the ultimate challenge. It’s relatively easy to track contacts as they move through the marketing funnel, but it’s much harder to connect them to actual revenue in the sales or accounting systems. I whined about this at length in June, so I won’t repeat the discussion. Suffice it to say that some sort of revenue measurement, however imperfect, is necessary for your testing, reporting, and program execution to be complete.

Whew, it’s good to have all that out of my system. As I said at the beginning, I did enjoy my little visit to the marketing trenches. Now, it’s goodbye to that world and hello to what’s next.

0 Eloqua SmartStart Speeds Marketing Automation Deployment, But It's Still Work

Summary: Eloqua's SmartStart gets marketers rolling in less than one week. It does require extensive preparation, but Eloqua leads you through that too. Let's face it, folks: putting a good demand generation program in place is real work.

Eloqua last week announced a money-back satisfaction guarantee for clients who participate in its SmartStart deployment program. Skeptical creature that I am, I wanted to hear the details before writing about it. By happy coincidence (OR WAS IT?), Eloqua Director of Key Accounts Jill Rowley scheduled a talk with me a few days later and filled me in.

SmartStart is a two-to-five day paid consulting engagement that helps new Eloqua clients fully deploy their systems. It’s not to be confused with the free QuickStart program (which I wrote about last May) which provides a smaller set of services. More than 150 Eloqua clients have now completed the SmartStart process, which is delivered by both Eloqua’s own professional services group and certified consulting partners.

The scope of SmartStart is indeed impressive. By the end of the program, marketers have initial email, forms, landing pages, Website tracking, CRM integration, reporting, and either lead scoring or nurturing programs. One key is preparation – the on-site sessions are preceded by extensive information gathering and technical groundwork, guided by Eloqua templates. This covers CRM integration, adding Web tracking scripts to company Web pages, assembling images and email formats, data cleansing, landing page subdomain set-up, specifying forms content and designing the lead scoring matrix. The process also includes a marketing maturity assessment that helps to define long term plans for improving the client’s marketing operations.

Rowley said most small companies can assemble the necessary information in a few days, although larger organizations take longer. Similarly, the SmartStart process itself works best for firms with relatively simple marketing operations, which Rowley said has less to do with size than numbers of regional offices and lead scoring programs, CRM integration, and existing automation. The single biggest challenge is the complexity of rules that govern CRM data synchronization, which can get very detailed when companies want different treatments in different situations.

The other key to the program is concentration during the SmartStart execution itself. The primary system administrator must devote full time to the project, while other users are brought in as needed. Because most policy decisions are made in advance, the company’s chief marketer doesn’t need to be constantly present.

The price of SmartStart varies from $4,000 to $19,000 depending on the version of Eloqua and type of CRM integration. Although that particular bit of information isn’t published, Rowley did point out to me that Eloqua’s Web site now shows basic price data, which used to be a closely-guarded secret. Pricing rules have also been vastly simplified.

That money-back guarantee? It’s good for six months and applies only to future portions of a subscription: so if you pay for a year and cancel after four months, you get refunded for the remaining eight months. That’s not quite a full refund, but it puts Eloqua on par with competitors who allow month-to-month agreements without an annual contract.

0 2010 Will Bring New Features to Demand Generation Systems

Summary: the demand generation market will continue to grow in 2010, and it may attract some new, big competitors from outside the industry. But the real excitement will be features that expand the scope of demand generation products to support inbound marketing, better measurement, and more efficient content creation.

2009 was a year of tremendous growth for demand generation systems (a.k.a. business-to-business marketing automation. By some measures, it's looking more mature: buyers are appearing outside the initial niche of software and technology companies; core functionality is well understood and largely consistent across products; vendors are expanding scope to include new users at existing accounts (in particular, sales departments); pricing is under pressure; and companies are starting to specialize in different customer segments.

On the other hand, there are still plenty of new entrants; few pioneering vendors have failed or consolidated; and related software vendors (in this case, CRM, email and Web site management systems) haven’t yet introduced me-too products. Perhaps most important, many potential buyers still don’t understand the value provided by these systems—although vendors are working very hard to educate them. So, on balance, I'd say the industry is still in a fairly early stage: late adolescence, if you will.

What will 2010 bring? Continued sales growth, for sure: that’s easy enough when you’re starting with a small base. We can also be confident that the feature trends I described in my review of 2009 will continue: better support for social media, greater access for sales departments, and more flexible reporting. I do expect vendors to converge on more standard social media features. These will probably combine the content-sharing and activity-tracking capabilities that different vendors now deliver separately.

There’s also a reasonable chance – although this prediction is less certain – that sales access features will blossom into deeper cooperation between marketing and sales in managing prospect relationships. There's no question in my mind that such cooperation will appear: it's inevitable as marketing’s role expands beyond lead generation to long-term relationship management. What I don’t know is how quickly this will happen or whether the sales access tools will be the connection point. One reason they might not is that sales access tools are used by individual sales people, while broad marketing and sales integration is likely to be controlled by senior sales management.

So much for the rear view mirror. Here are some predictions that are larger departures from the immediate past.

- me-too products. It's just a matter of time before CRM vendors (yes, I mean Salesforce.com) and Web content management vendors decide to compete seriously for marketing automation business. Frankly, this is so obvious that I'm almost embarrassed to mention it. But I wouldn't want anyone to say I failed to see it coming.

- inbound marketing. The work of generating Web traffic through search engine optimization, paid Web ads and expanded Web content has so far been performed outside of most demand generation systems. These are important marketing activities and they are a natural extension of demand generation systems, even though they require closer integration with (or replacement of ) Web content management and Web analytics. Note that Webinars and social media, which are also inbound marketing devices, are already being added to marketing automation products.

This type of extension—supporting new tasks for current users—is typical of maturing products once the core functions widely available. It also implies that vendors specializing in these areas will add their own marketing automation features to compete. HubSpot particularly comes to mind, which is a testament to their own marketing skills.

- external data. Many demand generation systems already make it easy to look up data about prospects from sources like Hoovers or JigSaw and to infer the location and company of anonymous visitors from their IP address. Certainly those features will continue to grow. But there’s another trend that's very pronounced in the consumer marketing space, which is using consumer panels and surveys to measure responses that aren’t captured within the company’s own systems. I haven’t seen much analogous activity among business marketers, but think that will change as the technique becomes more common and as business marketers accept that internal data will never provide all the answers they really need for effective marketing measurement. The task for the marketing automation vendors is making it easier to integrate such data and, in cases such as ad-embedded surveys, to generate it.

- content grazing. I'll explain that label in a moment. The idea is to squeeze the most value from existing marketing content, rather than creating new content for each project and situation. This implies two complementary tasks: being able to extract and classify nuggets of information from existing marketing documents, and being able to deliver exactly the right nugget in each situation.

The underlying insight is that there’s so much information available today that people don’t have time to digest large blocks of it. Rather, they want be fed bite-sized chunks that meet their immediate needs. Hence, the term "content grazing": it's like eating appetizers instead of a full meal.

Today’s marketing best practice is the opposite of content grazing: it’s to develop many different campaigns that deliver large volumes of content for different situations. This is expensive and it's exactly what prospects don't want. The alternative is automated systems that extract and classify content from existing materials, including many such as blog posts that would be created for other purposes. Other automated systems would can select and deliver the correct content during each interaction.

Basically this is the challenge of simulating a human conversation. It’s possible that some solutions will be based on automated customer service agents already used for other interactions. I haven’t seen this applied in a marketing automation context, but suspect it’s a path that marketers will be forced to explore as they recognize the full cost of conventional content-heavy approaches, and that buyers don't want them anyway.