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 LeadSpace Offers A No-Memory Approach to B2B Lead Scoring

My discussion last week of Infer, Mintigo, and Lattice Engines raised the question of what other B2B data vendors might be considered Customer Data Platforms. It’s easy to exclude companies that provide basic B2B lists (D&B, Data.com, Netprospex, ZoomInfo, etc.) since they’re clearly in a different business. But there’s another set of vendors that look very much like Mintigo, Infer, and Lattice Engines building detailed profiles by extracting data from Web sites, social networks, and other sources. This group includes InsideView, OneSource, SalesLoft and LeadSpace. So far as I know, none of them maintains a permanent copy of a client’s own customer file, which is the essence of being a Customer Data Platform. But if you’re a marketer needing to identify and score B2B prospects, you’d still want to give them a look.

I bring this up because a colleague suggested reconsider classifying LeadSpace as a CDP, which prompted me to learn more about them. Here’s what I found.

- LeadSpace, like the other vendors, scans Web sites, blogs, Twitter feeds, LinkedIn profiles, job hunting sites, and other sources to build a picture of a company’s business, managers, technologies, and similar attributes. Of course, every vendor argues it does this better than anyone else.  I  suspect there are indeed significant differences.  But I haven’t done any testing or seen anyone else’s test results – so all I can say is that wise buyers will test for themselves before making a choice.

- LeadSpace does build lead scores, something its Web site doesn’t reflect. This is one of the major points of differentiation among vendors in this space, so it’s worth understanding exactly what kind of scores each company provides. In LeadSpace’s case, the company builds “ideal buyer profiles” that measure how similar a lead is to a sample of existing customers provided by a client. Most clients have multiple profiles for different products or customer segments. Other companies in this group build different types of scores: say, for response to a specific campaign, or becoming a sales accepted lead, or having a high lifetime value. Some also estimate the incremental financial value of taking an action. It’s easy for buyers to gloss over these differences, but that would be a big mistake: they largely what kinds f applications a system can support. So be sure to explore them in detail (or read our explanations once we release the CDP Report itself.)

- LeadSpace doesn’t maintain its own permanent master database of all companies on the Internet. Rather, it conducts a fresh scan as each client requests research into its target audience.  This is another big difference from its competitors, who do run continuous scans and keep the results. LeadSpace argues that its approach avoids outdated information, saves the cost of storing and updating a persistent database, and lets the system collect precisely the right attributes for each situation – which can’t be known in advance. The company also points out that even a new scan will capture some history: the public Twitter feed goes back one year, as do job site listings. I have doubts about these arguments – I think older data can show important trends, am sure there’s plenty of outdated information on current Web pages, and suspect there’s the important attributes are pretty similar from one project to another.  Perhaps LeadSpace is really making the subtler argument that the incremental value of older information doesn’t justify the incremental cost of scanning and storing it, which is perfectly possible.  The company does store some old information, such as common job titles, to help analyze and classify inputs.

- LeadSpace doesn’t load a copy of its clients’ customer names, either. That’s essential for a CDP, which by definition has the potential of evolving into a primary marketing database. But it's not essential for LeadSpace's primary business of lead scoring, where even can be built on just a sample of a few hundred records. The arguments for and against the permanent master database also apply here, so I won’t repeat them. In addition, LeadSpace says its clients care more finding prospects with the right attributes, such as industry, company size, and technology fit, than trends in their behaviors or new job titles. Again, I’m not sure I agree, but should point out that LeadSpace mentioned combining their own scores with behavior data captured in marketing automation: so LeadSpace itself is at least implicitly acknowledging that behaviors are important.. LeadSpace's approach also means it can’t monitor a set of names and issue alerts when they do something interesting.  This is definitely something salespeople like to do. LeadSpace is closing that particular gap by developing a service, soon to enter beta testing, that will do a monthly scan of a client’s customer records.  It will feed the results back to the client's CRM or marketing automation, which themselves will highlight any changes.

- LeadSpace provides both prospect lists (i.e., new names) as well as data enhancement (i.e., information on names provided by the client). Most of its competitors also do both, but some do only enhancement. Again like its competitors, LeadSpace provides an interface for sales people to view the details associated with an existing customer. This is where its on demand approach comes in handy, since the interface can present information in categories tailored to each client’s needs. The system also lets sales people rate each lead with a thumbs up or thumbs down, providing feedback to fine tune the scoring model. I haven’t seen that particular feature in competitive systems but it’s not something I’ve specifically researched.

LeadSpace was founded in 2007 as a prospecting tool that let salespeople enter a company name and receive a list of individuals and their associated information and social conversations. The evolutionary path from there to the current system , launched in 2012, is fairly obvious. The company currently has more than 50 clients, mostly large B2B technology vendors. Pricing is based on the number of records either enhanced or provided in prospect lists, and starts around $25,000 per year.

0 Infer Keeps It Simple: B2B Lead Scores and Nothing Else

I’ve nearly finished gathering information from vendors for my new study on Customer Data Platform systems and have started to look for patterns in the results. One thing that has become clear is that the CDP vendors fall into several groups of systems that are similar to each other but quite different from the rest. This makes sense: most of the existing CDP systems were built to solve specific problems , not as general-purpose data platforms. Features will probably converge as vendors extend their products to attract more clients. But right now the groups are quite distinct.

One of these categories is systems for B2B lead scoring. I found three CDPs in this group: Lattice Engines (which I reviewed in April), Mintigo (reviewed in June), and Infer, which I'm reviewing right now.

Like the others, Infer builds a proprietary database of pretty much every company on the Internet by scanning Web sites, blogs, social media, government records, and other sources for company information and relevant events.  It then imports CRM and marketing automation data from its clients' systems, enhances the imported records with information from its big proprietary database, and builds predictive models that score companies and individuals on their likely win rate, conversion rate, deal size, and lifetime revenue.

The models are applied to new records as they enter a client’s system, creating scores that are returned to marketing automation and CRM to use as those systems see fit. The most typical application is deciding which leads should go to sales, be further nurtured by marketing automation,  or discarded entirely. But Infer customers also use the scores to prioritize leads for salespeople within CRM, to measure the quality of leads produced by a marketing program, assess salesperson performance based on the quality of leads they received, and even adjust paid search campaigns based on the quality of leads generated by each source and keyword.

Infer differs from its competitors in many subtle ways: the scope of its data sources, its matching processes to assemble company and individual data, the exact types of scores it produces, its modeling techniques, and reporting.  It also differs in one very obvious way: it returns only scores, while competitors return both scores and enhanced profiles on individual prospects.  Infer gathers the individual detail needed for such profiles, but has decided so far not to make them available. Its reasoning is that scores provide the major value from its system and profiles would detract from them – perhaps because sales people might ignore them scores in favor of profile data. Focusing on scores alone also makes Infer simpler to set up, operate, and understand.

Infer might be right, but it’s hard to imagine they'll will stick with this position once they start selling directly against competitors that offer scores plus profiles.  They will surely lose many deals for that reason alone.  On the other hand, Infer’s initial clients have been companies where free trials versions generate huge lead volumes, including Box, Tableau, NitroPDF, Zendesk, Jive and Yammer. Scores that accurately filter non-productive leads are more important to those companies than individual lead profiles.  Perhaps there are enough such firms for Infer to succeed by selling only to them.

Whether or not Infer expands its outputs, it faces another challenge: convincing buyers that its scores and data are better than its competitors. This might well be true: based on the information I’ve gathered, Infer seems to have a richer set of data sources and more sophisticated identity matching than at least some competitors. But my impressions may be wrong, and most buyers will won’t dig deeply enough to form an opinion.  Instead, their eyes will glaze over when the vendors start to get into the details, and they’ll simply assume that everybody’s data, matching, and modeling are roughly equivalent.

The only real way to measure relative quality is through competitive testing of which scores work better.  Each buyer needs to run her own tests since results may vary from business to business. How many buyers will take the time to do this, and which vendors will agree to cooperate, is a very open question.

That said, I did speak with some current Infer users, who were quite delighted with how easy it had been to deploy the system and with results to date. This is hardly a random sample – these were pioneer users (the system was only launched about a year ago) and hand-picked by the vendor. But their experience does confirm that performance is solid.

Infer pricing is based on the number of records processed and connected systems.  The vendor doesn’t reveal the actual rates but did say it is looking at options to make the system more affordable for smaller clients.

0 NitroMojo and Marketing Advocate Specialize in Marketing Automation for Channel Partners

As I noted in a post last year, there is a universe of specialized marketing automation systems for companies that sell through channel partners. These products address several interrelated challenges: distributing leads to partners without losing track of performance; distributing partner-customized versions of company-created content; and helping partners run their own marketing campaigns. Here are two more vendors with related offerings:

NitroMojo focuses primarily on lead distribution and tracking. Its particular strength comes from sending follow-up email surveys directly to leads to find out what happened: were they contacted by the channel partner? did they eventually buy? is there someone else at their company to talk to? is there something else they might purchase? This addresses one of the central dilemmas of selling through partners, which is losing contact with the leads and, as a result, not being able to measure effectiveness of corporate lead generation programs. NitroMojo says about 60% of leads reply to the surveys, giving enough information for meaningful analysis of program, partner, and salesperson performance.

The system also provides sales reps and sales managers with basic sales automation, including abilities to enter and rate new leads, review and prioritize existing leads, track call results, send materials from a central library, and schedule future calls. Corporate marketers can build campaigns with multiple events, create landing pages, capture revenues and costs, distribute leads with complex routing rules, score leads on behaviors and salesperson ratings, and measure performance.  Pricing starts around $3,000 per year plus $100 per user per month, which is usually less than the cost of marketing automation and sales automation systems that NitroMojo would replace. The current version of NitroMojo system was introduced about a year ago and had three global clients with more than 150 users when I spoke with the company in April.

Marketing Advocate is designed to help technology resellers who lack in-house marketing skills. It provides a resellers with a vendor-sponsored microsite that gives them access to marketing content, prospect lists, acquisition email campaigns, and automated nurture emails.  Resellers define their target prospects when they set up the system and then purchase suitable lists from suppliers including NetProspex, Jigsaw, and Harte-Hanks. These prospects, and other names uploaded by the reseller, receive standard campaign emails at three week intervals until they respond by visiting a landing page. The system then sends them personalized emails offering contents related to their behaviors. The leads are also scored and, when ready, can be passed to a telephone lead qualification service or directly to the vendor’s sales automation system. The sponsoring vendor doesn’t see the lead names until the reseller enters them into the system.

The point of all this is to minimize the effort that the resellers themselves must put into marketing. Marketing Advocate typically builds 25 to 30 prospecting campaigns tailored to different customer segments, and lets the resellers select the campaign and segments they want to pursue. The company also assembles and selects content to offer in the emails, has negotiated arrangements with the list providers, gives reports that analyze program response quantity and quality, and offers a concierge service to review results with resellers and discuss improvements. The system can also integrate with event management software and Google AdWords. Partner agencies are available for telephone lead qualification, search engine optimization, and paid search.

Marketing Advocate typically costs $500 to $700 per month per reseller, with some portion of the expense usually subsidized by the sponsoring vendor. Marketers pay $1 per name for prospects. The system is used by divisions at several major technology vendors including IBM, Microsoft, and HP.

0 NICE Buys Causata to Extend Its Customer Experience Management Position

So, there I was around 7:30 Eastern time this morning, sending out reminder notices to vendors I need to interview for an upcoming report on Customer Data Platforms. I received an immediate response from the Kevin Nix of Causata, offering to talk that very morning. This seemed a bit odd – Causata is based in San Francisco, so it was 4:30 a.m. local time and most people need more notice to schedule a call. But I had Things To Do, so I didn't give it much thought. Then, at the end of another call, a participant casually mentioned that Causata had just been purchased by Israel-based NICE Systems.  At first I was struck by the coincidence, and then realized what had happened: Nix was up because he had been talking to the folks in Israel, and he replied because he wanted to discuss his acquisition, not my report. [Insert image of deflating self-importance].

Sure enough, when I did dial in, I was treated to a prepared briefing on why NICE had made the deal.

There’s really nothing wrong with that. NICE is little-known in marketing circles, although I had bumped into them previously when they bought decision management vendor eGlue in 2010. But NICE is a major player in contact center systems, with nearly $1 billion revenue and $2.5 billion stock market capitalization. So I was pleased to connect with them directly and learn a bit more.

The briefing itself was interesting too. It turns out that while NICE still sells primarily to contact center managers, it is working hard to expand to clients in marketing, sales, compliance (it bought Actimize in 2007) and other areas related to customer experience. Its interest in Causata related to all  that, and in particular to that fact that Causata can capture Web interactions in real time and present them with related recommendations to contact center agents and other systems. This pumped me back up a bit, since it can be read as validation of the Customer Data Platform concept that I’ve been developing, which is about exactly this need to make customer data easily available across platforms. In fact, Causata was the original example I used to introduce the idea.

But enough about me, at least for the moment. The idea of NICE expanding to become an all-channel, all-department customer experience vendor immediately raises the question of how they’ll compete with all those other omni-everythings approaching from digital marketing (Adobe), B2B CRM (Salesforce.com), and general enterprise systems (Oracle, SAP, IBM). The contact center world has actually been a font of decision management systems, most notably Chordiant (now part of Pegasystems) and Infor Epiphany. So it’s certainly possible that they will be another source of competitors converging on the market for integrated customer experience management solutions. Like the CRM and Web content management vendors, the contact center firms start from a strong customer and financial base, making them formidable contenderss in what will surely be a long battle for high stakes.

I haven’t formed a solid opinion yet on how NICE in particular or contact center vendors in general are likely to fare in this new arena. But they are definitely something to factor into future assessments.