Customer Experience Matrix

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SalesPredict Offers Highly Automated, Highly Flexible Predictive Modeling

Customer Experience Matrix

Back in, say, 2008, a product like this would be big news. It then enhances the data with business and demographic information from public Web pages, social profiles, and third party sources including Zoominfo , InsideView , and Orb Intelligence. A couple of weeks ago, I wrote that “predictive everywhere” is one of major trends in data-driven marketing. Is SalesPredict right for you?

Sailthru Offers End-to-End Omnichannel Personalization for B2C Marketers

Customer Experience Matrix

Sailthru builds a history of information about individual customers. You might think that would be done by all personalization systems but it''s possible to do something that can reasonably be called “personalization” using only anonymous information such as traffic source, search terms, location, or Web pages viewed during a visit. This makes it extremely flexible, which is very important in the fluid world of marketing information. Sailthru was founded in 2008. This means that solution statements sound pretty much alike, even when the actual products are different.

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Optify Lets Agencies Provide Small Business with Marketing Automation, Distributed Marketing, and Sales Enablement

Customer Experience Matrix

sales enablement: systems to share marketing information with sales ( Genius , SalesFusion , LeadFormix , RightOn Interactive , Optify) distributed marketing: systems shared between central marketing organizations and local branches, dealers, distributors, sales agents, etc. dashboard lets users pick widgets to display selected information. That''s theme number three.

Pitney Bowes Interaction Optimizer and Dialogue Offer Unified Inbound/Outbound Marketing Campaigns

Customer Experience Matrix

Portrait itself brought an agglomeration of previous acquisitions, having expanded its original customer relationship management system by purchasing Quadstone analytics in 2005 and Million Handshakes marketing automation in 2008. Foundation integrates the information it gathers and passes it to IO through a Web services interface. Someone at Pitney Bowes clearly got the message.

Content Marketing Playbook: Strategy and Roadmap

Conclusion 31 Table of Contents ULTIMATE CONTENT STRATEGIST PLAYBOOK CONTENTLY3 In 2008, General Electric CMO Beth Comstock had just. of information. The primary source of information is specialized. source of information is specialized investment media and financial. ULTIMATE CONTENT STRATEGIST PLAYBOOK CONTENTLY1 The Ultimate Content Strategist. All rights reserved.

Balihoo Offers "Local Marketing Automation" for Channel Partners

Customer Experience Matrix

Users set up a “my info” page with contact information, store hours, directions, and other details. Even though customer data remains with the channel partner, Balihoo inserts tracking codes and captures aggregate response information so it can judge the effectiveness of different programs. Balihoo entered the “local marketing automation” business in 2008 and now has more than thirty enterprise clients serving more than 100,000 local businesses. These products are part of the marketing automation industry, although their specialized nature places them on the periphery.

A Framework for Real Time Decision Management: How SAS RTDM Fits In

Customer Experience Matrix

To gather this information systematically, I need a framework that lists standard features and options within those features. The connections are set up during system implementation and then used in real time to look up information about a specific individual during an interaction. I’ve had a couple of consulting projects recently that involve real-time decision systems (a.k.a.

Insights from Eloqua's IPO Registration Statement

Customer Experience Matrix

Client counts are reported only for 2008 through mid 2011. Operating expenses grew sharply through 2008, nearly outpacing revenue. In the absence of real information, I’ll just blindly speculate. Summary: Eloqua's registration statement offers new and interesting details about its business. My analysis is below. Eloqua’s was no exception. Let’s start with what they showed.

Sybase IQ: A Different Kind of Columnar Database (Or Is It The Other Way Around?)

Customer Experience Matrix

Much of this was spent updating my information on SybaseIQ , whose CTO Irfan Khan was a co-panelist. I spent a fair amount of time this past week getting ready for my part in the July 10 DM Radio Webcast on columnar databases. Sybase was particularly eager to educate me because I apparently ruffled a few feathers when my July DM Review column described SybaseIQ as a “variation on a columnar database” and listed it separately from other columnar systems. In truth, though, that original article was part of the problem. So there was no error in what I wrote. But I am not that someone.

eglue Links Data to Improve Customer Interactions

Customer Experience Matrix

As eglue captures information about an on-going interaction, it applies rules and scoring models to decide what to recommend. More important, they provide a useful range of information: the recommendation itself, selling points (which can be tailored to the customer and agent), a mechanism to capture feedback (was the recommended offer presented to the customer? Did she accept or reject it?), and links to additional information such as product features. Let me tell you a story. Then, finally, some studies came out the other way. Nice theory, though.)

Hard Data to Justify Your Marketing Automation Investment

Customer Experience Matrix

client asked yesterday if I had some benchmark information to justify the cost of her marketing automation project. Summary: So you want some hard numbers to prove the value of marketing automation? Here's a bunch. This set off an hour-long scavenger hunt through my hard drive, followed by sporadic afterthoughts later in the day. Since this is a question that comes up pretty often, I figured I’d share some of the more useful results. If anyone else cares to expand on this list, even better. 1. Neolane “ Making the Business Case for Enterprise Marketing Software ”. 32.2% 51% win rates 55.6%

Visualizing the Value of QlikTech (and Any Others)

Customer Experience Matrix

It's a little harder to read but perhaps the extra information is worth it. As anyone who knows me would have expected, I couldn't resist figuring out how to draw and post the chart I described last week to illustrate the benefits of QlikTech. The mechanics are no big deal, but getting it to look right took some doing. Usually this means it resides in a data warehouse or data mart.

Why Social Media Really Matters

Customer Experience Matrix

This matters because social media are an alternative gateway to finding Web content: instead of doing a search, I can ask my online community for information or recommendations. This is use of social media to connect with consumers. I’ll date it from 2008, although effective marketing uses of social media are just starting to emerge. Content is still important, of course, but its nature shifts from information that visitors consume to tools like widgets that empower them to share their enthusiasm with others. Social media is the latest stage in this evolution. authority.

A Modest Proposal for Demand Generation Usability Measurement

Customer Experience Matrix

The test packages would include score sheets to make capturing this information as easy as possible. 4. As Tuesday’s post suggested, my thoughts on usability measurement have now crystallized. To provide a meaningful and consistent comparison of usability across demand generation vendors, you could: 1. Define a set of business scenarios that must be supported by the system. Each scenario would describe a type of marketing campaign and the system tasks required to run it. These tasks would cover system set-up, materials creation, campaign design, execution and evaluation. sigh**.

Marketbright Targets Sophisticated Demand Generation Users

Customer Experience Matrix

The slides did list a few unusual features, including “prospect portals” that help buyers and sellers to share information related to a project; a sales proposal builder; and features to work with sales partners. still fear this could mislead by obscuring important information: for example, deep functionality in a few areas could generate the same score as limited functionality across many areas. I had a preliminary conversation last week with Mike Pilcher of Marketbright , one of the vendors I’ll probably end up adding to the Raab Guide to Demand Generation Systems.

Measuring Usability: A Task-Based Approach

Customer Experience Matrix

This is another convenient conclusion, since statistically meaningful surveys would require finding a large number of demand generation system users and gathering detailed information about their levels of expertise. I think we all know that the simplest practical measure of intelligence is how often someone agrees with you. On that scale, University of Ottawa Professor Timothy Lethbridge must be some kind of genius, because his course notes on Software Usability express my opinions on the topic even better and in more detail than I’ve yet to do for myself. But I knew that already. 2.

Usability Is Just One Piece of the Puzzle

Customer Experience Matrix

Of course, this does raise the question of whether the feature information assembled in the Raab Guide to Demand Generation Systems is really helpful. What the Guide really does is save readers the work of assembling all the feature information for themselves, thereby freeing them to focus on defining their own business processes, tasks and users. A funny thing happened as I was writing one of my usual rants on incorporating usability into the selection process. The resulting paper is on the [link] site, creatively titled "Building Usability into Your System Selection".)

LucidEra and Birst Blaze New Trails for On-Demand BI

Customer Experience Matrix

Apparently, many marketers never learned how to analyze the information buried within their sales automation systems, simply because it wasn’t available back when they were being trained. I spent a few minutes last week on the Web sites of about eight or nine on-demand business intelligence vendors, and within a few days received emails from two of them ostensibly asking about much earlier visits where I must have registered with my email address. suppose I should admire this as good marketing, although the disingenuousness of the messages was a bit disturbing. Whatever.

Department of the Obvious: Anti-Terrorist Data Mining Doesn't Work

Customer Experience Matrix

Actually, I've never seen 24 , so I don't really know what claims it makes for technology.) So even though this is outside the normal range of topics for this blog, it's worth publicizing a bit in the hopes of stimulating a more informed public conversation. I've emerged from the cave where Osama bin Laden and I were working on the new Guide to Demand Generation Systems (oops -- the Osama part was supposed to be secret) and am now catching up with the rest of the world. See " Government report: data mining doesn't work well " from CNET.

More Thoughts on Comparing Demand Generation Systems

Customer Experience Matrix

When I looked at the various items of information I have been gathering, it was pretty easy to determine where in this matrix each item belonged. I have mostly been focused this week on formats for the new Demand Generation Guide. Since this is of interest to at least some regular readers of this blog, I suppose it’s okay to give you all an update. The issue I’m wresting with is still how to present vendor summaries. As of last week’s post , I had decided to build a list of applications plus some common issues such as vendor background, technology and pricing.

Infobright Puts a Clever Twist on the Columnar Database

Customer Experience Matrix

The trick is that BrightHouse stores descriptive information about each data pack and can often use this information to avoid loading the pack itself. For example, the descriptive information holds minimum and maximum values of data within the pack, plus summary data such as totals. Subsequent queries can use this information to avoid opening data packs unnecessarily. The system was officially launched in early 2008 and now has about dozen production customers. Note: Per Susan Davis' comment below, they have since reloaded it here.]

Still More on Assessing Demand Generation Systems

Customer Experience Matrix

This is no reflection on the product, which seems to be well designed, is very reasonably priced, and has a particularly interesting integration with the Jigsaw online business directory to enhance lead information. This involves a fair amount of work beyond gathering information about the vendors themselves, but I suppose that’s what it takes to deliver something useful. I had a very productive conversation on Friday with Fred Yee, president of ActiveConversion , a demand generation system aimed primarily at small business. Anyway, back to our talk.

Raab on DM Radio Panel on July 10

Customer Experience Matrix

For more information and to register, visit [link I'm scheduled to appear on a DM Radio panel on columnar databases on July 10. I'll be joining Dr. Michael Stonebraker, architect of the modern INGRES and POSTGRES database designs, and CTO/Founder of columnar database developer Vertica, and several additional guests.

More Blathering About Demand Generation Software

Customer Experience Matrix

When I was researching last week’s piece on Market2Lead , one of the points that vendor stressed was their ability to create a full-scale marketing database with information from external sources to analyze campaign results. But I recently spoke with on-demand business intelligence vendor LucidEra , who also said they had found that demand generation systems could not integrate such information. In the meantime, the Aberdeen report provided some other interesting information. plan to write more about LucidEra next week.) The question is how you interpret this.

The Value of Intra-Site Web Search: A Personal Example

Customer Experience Matrix

NewEgg has to somehow populate its checkboxes with all that information. I’ll do a real post later today or more likely tomorrow, but I thought I’d quickly share a recent personal experience that illustrated the importance in e-commerce of really good in-site search. By way a background: having a good search capability is one of those Mom-and-apple-pie truths that everyone fully accepts in theory, but not everyone bothers to actually execute. Anyway, I recently needed a notebook PC with a powerful video card for gaming on short notice. Or, at least, one of my kids did.

For Behavior Detection, Simple Triggers May Do the Trick

Customer Experience Matrix

The type of behavior tracking I wrote about last week—seeing which pages a visitor selected, what information they downloaded, how long they spent in different areas of the site, how often they returned, and so on—often relates to large, considered purchases. Information such as comparisons with competitors may be popular but could lead them to delay their decision or even end up purchasing something else. The business issue is how to make the best use of the information about detailed Web (and other) behaviors. But this simple condition is not always met.

Market2Lead Offers Enterprise-Strength Demand Generation System

Customer Experience Matrix

It can support programs in 42 languages, store a default language for each prospect, and capture information in different languages from the same person. Market2Lead offers the usual list of demand generation functions: outbound email, Web forms and landing pages, automated lead nurturing, integration with sales, and campaign return on investment analysis. But while many demand generation vendors simplify these features so marketers can run them for themselves, Market2Lead offers no such compromises. This is not to say that Market2Lead is especially hard to use. But it’s just fine.

Demand Generation Systems Shift Focus to Tracking Behavior

Customer Experience Matrix

The (true) claim is that this information gives a significant insight into the prospect’s state of mind: the exact issues that concern them, their current degree of interest, and which people at the prospect company were involved. Of course, the Web information is combined with conventional contact history such as emails sent and call notes to give a complete view of the customer’s situation. The greater volume of information now available implies a much larger number of possible decisions, so a new approach is needed. But I suppose it’s not a real privacy violation.

Denodo Helps Mesh Enterprise Data

Customer Experience Matrix

The main marketing application of this work has been building business and consumer profiles with information from public Web sources. Basically their approach is to build specialized connectors, called “wrappers,” that (a) extract specified information from databases, Web sites and unstructured text sources, (b) put it into queryable structure, and (c) publish it to other applications in whatever format is needed. On the other hand, eglue offers richer features for presenting information to call center agents. Whether this is literally true or not (and who could know?),

WiseGuys Gives Small Firms Powerful List Selection Software

Customer Experience Matrix

The data import takes incremental changes in the source information – that is, new and updated customers and new transactions – rather than requiring a full reload. The system will combine the transaction history of the duplicates, but not move information from one customer record to another. This means that if the surviving record lacks information such as the email address or telephone number, it will not be copied from a duplicate record that does. But the majority of businesses have nowhere near the resources needed to manage such systems. Let’s start at the beginning.

Bah, Humbug: Let's Not Forget the True Meaning of On-Demand

Customer Experience Matrix

These also take customer lists submitted over the Internet and automatically return enhanced versions – in their case, IDs that link duplicates, postal coding, and sometimes third-party demograhpics and other information. I was skeptical the other day about the significance of on-demand business intelligence. still am. But I’ve also been thinking about the related notion of on-demand predictive modeling. Any modeler will tell you that fully automated systems make errors that would be obvious to a knowledgeable human. Call it the Sorcerer’s Apprentice effect. third-party databases).

Service Oriented Architectures Might Really Change Everything

Customer Experience Matrix

The four reader comments posted so far have been not-so-politely skeptical of this notion, basically because they feel IT will still do all the heavy lifting of building the databases that provide information for these user-built systems. I put in a brief but productive appearance at the DAMA International Symposium and Wilshire Meta-Data Conference running this week in San Diego. This is THE event for people who care passionately about topics like “A Semantic-Driven Application for Master Data Management” and “Dimensional-Modeling – Alternative Designs for Slowly Changing Dimensions”.

What's New at DataFlux? I Thought You'd Never Ask.

Customer Experience Matrix

The new developments also encompass product information and other types of non-name and address data, usually labeled as “master data management”. Of course, DataFlux does use rules and reference information when appropriate. What with it being Valentine’s Day and all, you probably didn’t wake up this morning asking yourself, “I wonder what’s new with DataFlux ?” That, my friend, is where you and I differ. Except that I actually asked myself that question a couple of weeks ago, and by now have had time to get an answer. Which turns out to be rather interesting. Back to governance.

Fitting QlikTech into the Business Intelligence Universe

Customer Experience Matrix

First, some context. I’m using “business intelligence” in the broad sense of “how companies get information to run their businesses”. Quality” raises its own issues of definition, but let’s view this from the business manager’s perspective, in which case “quality” means something along the lines of “producing the information I really need”. We can put cost aside for the moment, because the out-of-pocket expense of most business intelligence solutions is insignificant compared with the value of getting the information they provide. This all seems reasonable enough. Sorry.)

Lyzasoft: Independence for Analysts and Maybe Some Light on Shadow IT

Customer Experience Matrix

On the other hand, Lyza is a young product (released September 2008) with only a dozen or so clients, so bugs would not be surprising. Reports show which users send and receive data from other users, as well as which data sets send and receive information from other data sets. QlikView has a very fast, scalable database and excellent tools to create reports and graphs.

Show Me the Numbers: Hard Data on Internet Use and Media Spend

Customer Experience Matrix

This showed that as of December 2008, search was still the most common Internet activity (used by 85.9% of the online population), compared with just 65.1% for email. Netpop Research reinforces this point in Media Shifts to Social , which found that as of September and October 2008, communications (including email, instant messaging, blogs and photo sharing) had risen to 32% of online time from 27% in 2006. By contrast, the Pew Internet & American Life Project Survey in December 2008 found only 35% of adult online Americans had a social media profile.

Demand Generation Implementation Survey - Background Results

Customer Experience Matrix

nbr responses vendor 8 Marketo 6 Eloqua 3 Genius.com 3 LoopFuse 3 Pardot 2 Market2Lead 2 Treehouse Interactive 1 eTrigue 1 Vtrenz (Silverpop) 7 No Response 36 Another intriguing bit of contextual information is the deployment date of the systems. There was actually another dated 6/01/2208, which I treated as 2008. I was also curious to see the six responses for implementations during 3/09 and 4/09; obviously, these companies haven't gotten past their first or second month. I've been having a dandy time analyzing the results of my Demand Generation Implementation Survey.

Youcalc: On-Demand Analytics Without Stored Data

Customer Experience Matrix

second, more fundamental limitation is that the system can’t access historical data, such as point-in-time snapshots of information which is not retained in operational systems. Youcalc was launched in its current form at the end of 2008, although the company has been working on its core technologies since 2003. Summary: Youcalc is an on-demand analytics vendor with 130 prepackaged applications primarily for sales and marketing reporting. Unlike its competitors, youcalc it reads data directly from other Software-as-a-Service systems rather than loading it into its own database.

Alterian Pushes Into Social Media Management with Techrigy Acquisition

Customer Experience Matrix

Previous acquisitions include Web content management (MediaSurface, 2008), contact optimisation (Campaign Calculus 2.0, Users can then select an article and drill into its details, including extracted Web site information and traffic rank, content analysis showing sources of the system-applied tags, the full article itself, and links to Alexa , Technorati , Compete and Quantcast information about the article source. Users can also delete the entry, mark it as spam, adjust the system-assigned tags, and edit information about the author. Others are sure to follow.

Hubspot Offers Small Business Marketers a Big Bundle of Features

Customer Experience Matrix

I've since been informed that Personality Grader was an April Fool's joke.]) The scope of Hubspot makes it somewhat difficult to assess. But it added Salesforce.com integration in 2008, which also meant the leads and their activity history could be shared with sales people. Summary: Hubspot offers a bundle of Web traffic generation and lead management features in one low-cost package. Small businesses willing to invest some effort should be pleased with the results. Of course, these multi-function systems must still be suited to users with little time and expertise.

Act-On Software Does List-Based Demand Generation

Customer Experience Matrix

For more information, see my blog post on Marketbright and my post on Treehouse International.) Act-On released its beta version in June 2008 and started selling last October. Most are small or mid-sized, but they also include Cisco , which invested in Act-On in 2008. If you look at the Web site of Act-On Software , you’ll see a typical set of demand generation features: email marketing, demand generation (equated with landing pages and forms), lead nurturing, Website visitor tracking, channel (partner) marketing, and lead scoring. It’s pretty limited.

LeadLife Mixes Advanced and Simple Features

Customer Experience Matrix

It follows some principles I first heard many years ago, the gist of which was to divide the screen into fixed regions that always display the same type of information (e.g., LeadLife was established in 2006 and released its first version in September 2008. I have my little checklist of features to define whether a demand generation system is suited for simple or complex marketing programs. You'll find most of the list in our report on Vendor Usability Scores on the Raab Guide site.) Sadly, some vendors didn't get the memo and have built products that straddle my categories.

Salespeople: One Question Matters Most

Customer Experience Matrix

The two clearest answers came from questions about the information salespeople want and why they don’t follow up on inquiries. By far the most desired piece of information about a lead was purchasing time frame: this was cited by 41% of respondents, compared with budget (17%), application (15%), lead score (15%) and authority (12%). Note that none of listed categories included behavioral information such as email clickthroughs or Web page visits, which demand generation vendors make so much of. doubt they would have ranked highly had they been included.

58.15 μs: 673.0 ns, 33.19 μs, 170.0 ns 444.8 ms: 546.8 μs, 5.819 ms, 436.2 ms