Last week’s post looked at newer marketing automation systems that focused on small businesses. They shared a similar approach of offering limited features in exchange for lower cost: messaging was largely limited to emails (except in Salesformics) and campaign flows were basically linear. The general notion is that small businesses are finding existing marketing automation products too hard to use and would be happy with something simpler, especially if it costs less.
Although this approach is popular, there are others. Here are a few options.
MindFire Studio grew out of MindFire’s original Look Who’s Clicking software, which is used by more than 1,100 printers and other graphics arts vendors to add personalized URLs to print promotions. Studio, released in mid-2012, lets those firms offer full marketing automation capabilities to their clients and is also sold directly to corporate marketers. The system supports email, print, SMS, Twitter, and voice messages, typically delivered via integration with third party systems. It also provides the rest of the standard marketing automation functions, including landing pages and microsites, Web behavior tracking, lead scoring, and integration with Salesforce.com. The approach is organized around events, such as an email open or click: there are different events for different channels, and each event can be assigned points for lead scoring, goals for behavior tracking, and costs for reporting. Events also act as triggers for actions within workflows, which begin with contact lists and can be filtered based on attributes and behaviors. One quirk is that the system reacts to all event-based triggers, rather than following a single branch within a workflow. This means that filters must be carefully crafted to avoid sending too many messages to the same person.
MindFire provides prebuilt templates for common marketing programs, to further assist clients who need help using the system. It doesn’t currently provide email or landing page builders, since its graphics arts clients typically had such tools already. It will be adding these as it sells more to corporate marketers, who tend to need them. Studio also provides other features suited to agencies or large corporate marketing departments, including multiple subaccounts, digital asset management, collaboration, and detailed user rights management. Pricing is based on the number of contacts and messages sent; it starts at $500 per month for corporate users with up to 10,000 contacts. Agencies can create their own branded version of the system and have full control over what they charge their customers.
SharpSpring also started as a narrow application – in this case, Web visitor identification and analytics – and evolved into a full marketing automation platform selling through agencies. The current system, launched mid-2013, includes the full set of standard features: email including templates that can be locked down in sections to prevent unauthorized changes; landing pages built and managed within the system or from external vendors including formstack, GravityForms, Wufoo, SugarCRM, or Salesforce.com; Web behavior tracking using Javascript tags; lead scoring based on attributes and behaviors; workflow using plain English statements rather than diagrams and supporting basic triggers, filters, actions and multiple steps but no branching; and CRM integration with Salesforce.com today and SugarCRM and ZohoCRM soon. The system also offers its own CRM – a useful option for agencies who might need to provide a low cost system to some clients, while accommodating others that have a system in place.
Other advantages include Google Adword integration; tagging leads by search term and Facebook ad; integration with Webex and GoToWebinar for event management; and a partnership with ZoomInfo to add contact names from companies that visit the client’s Web site. SharpSpring has built an exceptionally simple interface, featuring a single “new” button to add any type of object, screen overlays to illustrate available features and link to instructional videos, and real-time display of emails and forms as they are built. It supports agency clients with multi-account sign-on, precise user rights management, and exceptionally low pricing, beginning at $500 per month for up to five agency clients. Non-agency pricing starts at $200 per month for up to 500 contacts and reaches $800 per month for unlimited contacts.
SimplyCast is yet another multi-channel system, although it was designed that way from its start in 2010 and – quite unusually these days -- uses its own messaging tools rather third party systems. In fact, the vendor says it has sold more than one million separate subscriptions for email, auto-response, fax, SMS, voice broadcast, surveys, Web forms, landing pages, Web tracking, events, Twitter, and Facebook marketing, at prices starting from $3.00 to $9.99 per month. The integrated solution, SimplyCast 360, combines many of these with a unified customer database and workflow engine for $99 per month and up. Simple contact management is built into the system, or users can integrate with Salesforce.com, vTiger, SecondCRM, Wordpress, and Zoho. Clients who don’t want to use SimplyCast tools for a particular function can integrate with external products via APIs. The only standard marketing automation function that’s missing is lead scoring, which is due for release next month. The workflow engine has a graphical interface, multiple steps and query-based branching, although users must manually ensure branch conditions are mutually exclusive to avoid multiple executions. The vendor says that between 3,000 and 5,000 clients use SimplyCast 360. The $99 per month rate includes the base features and up to 500 active contacts; adding 10,000 active contacts would cost $500 per month more. There are also some other fees related to advanced features and certain message types.
Inbox25 began as an email system, used primarily as a module for SugarCRM. It launched its full-scale marketing automation system last fall. This provides reasonably powerful versions of the standard marketing automation features: email, landing pages and forms, Web tracking, lead scoring, workflow, and real-time synchronization with SugarCRM. Integration with other CRM systems is due soon. There is some social behavior tracking and detailed reporting on movement through buyer stages, as defined by score ranges. Workflow supports multiple steps linked to conditions defined by email, Web, and social behaviors, lead scores, and various attributes. Steps can execute actions within the system, including sending emails, updating scores and other data, adding to lists, and sending changes to the CRM system. What’s missing is connecting with other execution systems to send messages or import data, although this could be done via APIs or HTTP posts. The workflow doesn’t do true branching, defined as sending contacts down different paths within a single flow. But it does let users specify how contacts move through each flow, with options that include rechecking the original selection condition each time a step is executed, checking only the condition of the current step before it is executed, and checking all conditions up to the current step before it is executed. Inbox25 also recently added a “contact stream” option, similar to Marketo’s engagement engine, that scans a prioritized list of content at regular intervals and sends each contact the highest-priority item they haven’t seen before. Pricing for the marketing automation system starts at $99 per month for up to 250 active contacts. A more robust 12,500 active contacts costs $615 per month.
To summarize a bit: all these new systems stress low cost and ease of use. Some achieve modest improvements in usability by departing from traditional interfaces, but the real gains come from reducing functionality: the simplest systems avoid branching within multi-step sequences and support only email messaging. The other big difference among systems is whether messaging, CRM, and other functions are handled by the vendor’s own tools or by integrating with third party products. Some systems rely exclusively on internal or external tools, while others include their own tools but add APIs that support external integration as an alternative. Finally, there's a flowering of systems designed to let marketing agencies use the product for multiple clients. This type of specialization is both a sign of industry maturity and recognition that many marketing departments, especially at small companies, lack the resources to run advanced marketing automation by themselves.
This is the blog of David M. Raab, marketing technology consultant and analyst. Mr. Raab is founder and CEO of the Customer Data Platform Institute and Principal at Raab Associates Inc. All opinions here are his own. The blog is named for the Customer Experience Matrix, a tool to visualize marketing and operational interactions between a company and its customers.
Friday, January 31, 2014
Wednesday, January 22, 2014
Next-Generation Marketing Automation Systems Target Small Business
I’ve been gearing up for the next edition of our VEST report on B2B marketing automation systems, which involves catching up with established vendors and chasing down some new ones. The new entrants are clustered towards the small business end of the market, where they see an opportunity for simpler systems at lower prices than existing market leaders. I always wonder whether newcomers can find substantially simpler approaches than the older firms, which are already focused on ease of use and typically gone through several redesigns as they learn from experience. But it’s still worth scanning the new entrants to see how they’ve departed from older approaches. It’s also interesting to see how the new systems are similar, which gives some insight into what are apparently perceived as common problems in the older approaches.
Before jumping into the new systems, it helps to define a set of standard features to measure them against. I’ve written about this extensively in the past, so I won’t go into great detail here. Briefly, a standard B2B marketing automation system can send bulk emails to segmented lists, capture email responses on landing pages and forms, track email and Web site behaviors, score leads based on behaviors and profile attributes, execute multi-step workflows (i.e., nurture campaigns), and share leads with a CRM system like Salesforce.com. Not quite standard but increasingly common features include social media sharing and tracking, Webinar integration, visitor identification via reverse IP lookup, and capturing campaign information from Google AdWords. A system can be useful even if it lacks some of the standard features, but buyers should know what they’re missing so they can decide whether it’s something they really want.
Here are highlights of several vendors I’ve looked at recently. I’ll write about some others next week and then offer some general observations.
Leadsberry is among the oldest of these systems, launched in July 2012. It basic versions of the standard marketing automation features: lists are not updated automatically, workflows only branch on email behavior (opens, clicks, or nothing), and lead scoring is largely limited to profile attributes. On the other hand, it adds a powerful survey tool, easy conversion of emails to Facebook, Twitter, and LinkedIn messages, and easily created “instant offers”. Looking beyond technology, the vendor provides access to a 15 million name email database, a telephone lead generation team, and other services that can supplement or even replace an in-house marketing department. System pricing starts at $99 per month for up to 1,000 contacts; a system with 15,000 contacts costs $499 per month. There are additional fees for survey responses, list rental, and other services.
Leadsius launched its first paid version around July 2013. Like several of the new vendors, it is based in Europe (Sweden), although the user interface is in English. The system includes email, landing pages and forms, and Web behavior tracking. Workflows are currently limited: triggers are based only on email and Web activities, segments are defined only with profile attributes, and the only actions are emails. The next release will support list-based triggers and additional actions. Workflows can execute multiple steps but only branch on whether the previous email was opened. Synchronization with Salesforce.com and SugarCRM are due by mid-2014. Lead scoring is not available and probably won’t be added any time soon, because the developer feels it is dangerous without validating that scores are accurate. Among its strengths, the system provides detailed control over the rights assigned to different users; premium clients can have their own domain for landing pages and IP address for emails; and lists can be dynamic (i.e., continuously updated) as well as static. Leadsius comes in several versions including a free edition with a good set of basic features. New pricing in mid-February will retain the free version and introduce several other levels, most under $1,000 per month.
Salesformics is designed primarily to give sales people a pleasant-to-use CRM system, while offering marketing automation and dashboards to everyone in the organization. The system was developed by a UK-based marketing services firm and is still in public beta, which should end in mid-February. In a relatively radical departure from standard interfaces, it replaces traditional menus with a search box that lets users type commands or contact information (name, address, phone, etc.) and have the system return the best matching results. The system is also unusually reliant on third-party applications – dare we say “platform”? – using external systems to trigger promotions (for example, executing targeted searches in Twitter or LinkedIn to find contact-related events), to capture data (via externally-built web forms), and to deliver messages (email via Constant Contact or SMS via Twilio). Data from those sources, as well as the built-in CRM functions, can be used to create campaign segments. Indeed, the only traditional marketing automation functions provided by Salesformics itself are workflow and basic (untracked) email. Otherwise, trackable email and forms are provided via integration, there is no cookie-based Web behavior tracking, and lead scoring is not yet available (though planned). There is no synchronization to any external CRM system since Salesformics includes its own. The workflow uses a conventional diagram of triggers linked to actions; the triggers and actions are based on both internal and external data. A workflow can include multiple steps but branching won’t be supported until mid-2014. Pricing is based on number of users and starts at $79 per user per month.
Target360 was also developed by a UK-based service firm, in this case CRM consultants specializing in Microsoft Dynamics. The system adds email marketing and campaign tracking to Dynamics, working with Dynamics files directly rather than synching to a separate database. Among U.S-based firms, CoreMotives and ClickDimensions take a similar approach. Of the standard marketing automation functions, Target360 provides email, Web behavior tracking, lead scoring, and workflows. There is no form builder but the vendor provides a tool to map existing forms to the Dynamics database. Campaign workflows can only react to an email result, with separate branches for opens, clicks, and no response, although standard Dynamics workflows could support other actions as well. The system’s particular strength is tracking customer activities across different channels by assigning them campaign codes; this covers emails, Web visits, social media responses, and CRM interactions. These are connected with revenue captured in CRM to create return on investment reports. Revenue can be attributed in these reports to either the first or last campaign to reach a customer. The system was released in mid-2012 and starts at $1,050 per month including a Dynamics license.
Before jumping into the new systems, it helps to define a set of standard features to measure them against. I’ve written about this extensively in the past, so I won’t go into great detail here. Briefly, a standard B2B marketing automation system can send bulk emails to segmented lists, capture email responses on landing pages and forms, track email and Web site behaviors, score leads based on behaviors and profile attributes, execute multi-step workflows (i.e., nurture campaigns), and share leads with a CRM system like Salesforce.com. Not quite standard but increasingly common features include social media sharing and tracking, Webinar integration, visitor identification via reverse IP lookup, and capturing campaign information from Google AdWords. A system can be useful even if it lacks some of the standard features, but buyers should know what they’re missing so they can decide whether it’s something they really want.
Here are highlights of several vendors I’ve looked at recently. I’ll write about some others next week and then offer some general observations.
Leadsberry is among the oldest of these systems, launched in July 2012. It basic versions of the standard marketing automation features: lists are not updated automatically, workflows only branch on email behavior (opens, clicks, or nothing), and lead scoring is largely limited to profile attributes. On the other hand, it adds a powerful survey tool, easy conversion of emails to Facebook, Twitter, and LinkedIn messages, and easily created “instant offers”. Looking beyond technology, the vendor provides access to a 15 million name email database, a telephone lead generation team, and other services that can supplement or even replace an in-house marketing department. System pricing starts at $99 per month for up to 1,000 contacts; a system with 15,000 contacts costs $499 per month. There are additional fees for survey responses, list rental, and other services.
Leadsius launched its first paid version around July 2013. Like several of the new vendors, it is based in Europe (Sweden), although the user interface is in English. The system includes email, landing pages and forms, and Web behavior tracking. Workflows are currently limited: triggers are based only on email and Web activities, segments are defined only with profile attributes, and the only actions are emails. The next release will support list-based triggers and additional actions. Workflows can execute multiple steps but only branch on whether the previous email was opened. Synchronization with Salesforce.com and SugarCRM are due by mid-2014. Lead scoring is not available and probably won’t be added any time soon, because the developer feels it is dangerous without validating that scores are accurate. Among its strengths, the system provides detailed control over the rights assigned to different users; premium clients can have their own domain for landing pages and IP address for emails; and lists can be dynamic (i.e., continuously updated) as well as static. Leadsius comes in several versions including a free edition with a good set of basic features. New pricing in mid-February will retain the free version and introduce several other levels, most under $1,000 per month.
Salesformics is designed primarily to give sales people a pleasant-to-use CRM system, while offering marketing automation and dashboards to everyone in the organization. The system was developed by a UK-based marketing services firm and is still in public beta, which should end in mid-February. In a relatively radical departure from standard interfaces, it replaces traditional menus with a search box that lets users type commands or contact information (name, address, phone, etc.) and have the system return the best matching results. The system is also unusually reliant on third-party applications – dare we say “platform”? – using external systems to trigger promotions (for example, executing targeted searches in Twitter or LinkedIn to find contact-related events), to capture data (via externally-built web forms), and to deliver messages (email via Constant Contact or SMS via Twilio). Data from those sources, as well as the built-in CRM functions, can be used to create campaign segments. Indeed, the only traditional marketing automation functions provided by Salesformics itself are workflow and basic (untracked) email. Otherwise, trackable email and forms are provided via integration, there is no cookie-based Web behavior tracking, and lead scoring is not yet available (though planned). There is no synchronization to any external CRM system since Salesformics includes its own. The workflow uses a conventional diagram of triggers linked to actions; the triggers and actions are based on both internal and external data. A workflow can include multiple steps but branching won’t be supported until mid-2014. Pricing is based on number of users and starts at $79 per user per month.
Target360 was also developed by a UK-based service firm, in this case CRM consultants specializing in Microsoft Dynamics. The system adds email marketing and campaign tracking to Dynamics, working with Dynamics files directly rather than synching to a separate database. Among U.S-based firms, CoreMotives and ClickDimensions take a similar approach. Of the standard marketing automation functions, Target360 provides email, Web behavior tracking, lead scoring, and workflows. There is no form builder but the vendor provides a tool to map existing forms to the Dynamics database. Campaign workflows can only react to an email result, with separate branches for opens, clicks, and no response, although standard Dynamics workflows could support other actions as well. The system’s particular strength is tracking customer activities across different channels by assigning them campaign codes; this covers emails, Web visits, social media responses, and CRM interactions. These are connected with revenue captured in CRM to create return on investment reports. Revenue can be attributed in these reports to either the first or last campaign to reach a customer. The system was released in mid-2012 and starts at $1,050 per month including a Dynamics license.
Monday, January 13, 2014
Understanding Relationships Within the Marketing Technology Landscape
Scott Brinker, a.k.a. chiefmartec*, last week published a terrific Marketing Technology Landscape Supergraphic organizing nearly 1,000 vendors into 43 categories and six major classes. As Scott modestly writes, his classes present “a semblance of meaningful structure” with Internet and Infrastructure providing the foundations, Marketing Backbone platforms (major channel systems) managing most interactions, Marketing Middleware (including Customer Data Platforms) providing a connective layer, and Marketing Experiences and Marketing Operations systems offering specialized capabilities. Here is his diagram:
I’m delighted that Scott has found the CDP concept useful† and am in turn happy to adopt his distinction between Backbone Platforms and the other types of marketing applications. The Backbone Platforms are, indeed, platforms that support most Experience and Operations systems, enabling those systems to focus on particular tasks without creating complete customer management environments of their own. That's a difference worth noting.
Scott never claimed that his diagram illustrates a precise relationship among the components, so it's no criticism to point out that it doesn't. Experience and Operations systems sometimes connect with Backbone Platforms through a Middleware system, but more often they connect with the Backbone Platforms directly. In fact, some of the Experience and Operations systems connect with multiple Platforms, serving as sort of do-it-yourself Middleware. The challenge of illustrating this becomes clear when you try adding lines to show how the classes of systems interact with each other – it’s not as simple as connecting the adjacent layers on Scott’s diagram.
Being a visual thinker, I found this ambiguity to be endlessly disturbing.** Try as I might, I couldn’t rearrange the boxes to show the relationships correctly.
Then, I had a dream about a snake rolling downhill with its tail in its mouth, and discovered the answer: the systems could all be arranged in a circle graph, allowing any two to be connected directly.††
I must admit that I am ridiculously pleased with this approach. I know there’s nothing especially brilliant about circle graphs per se, but I’ve never seen one used in an architecture diagram. The pictures below illustrate, at least to my satisfaction, how much more clearly the circle graph shows relationships among systems than the traditional boxes and layers. Each diagram shows the same relationships among a small set of systems. The top left picture uses the traditional approach of showing only the links between categories – as you see, this hides any connections between non-adjacent components or individual systems. The top right picture shows the direct connections between systems, but it’s hard to read because lines cross behind the boxes. True, you could use curved lines to avoid this, but that quickly becomes impractical. The bottom picture shows the circle approach: here, the lines themselves might cross but no connections are hidden. The relative clarity of the circle graph grows as more systems are introduced.
Showing the actual connections between system pairs has another advantage: it lets you represent the architecture as a formal graph, meaning you can compare architectures using standard graph analysis techniques. Even just counting the connections gives a useful measure of relative complexity.
The diagrams below illustrate this nicely: the top picture shows the same architecture as before, which has 14 system-to-system connections (out of 28 possible pairs, another useful metric, even though some wouldn't make much sense). The bottom picture shows the same systems with everything connecting through a central database: now there are only eight connections and several missing system-to-system links have been provided automatically. If you want a crude approximation of how much a central database reduces complexity (and hence cost), this is good place to start.
The circle approach has other advantages, such as making it easier to see missing connections between systems. I'm working on it as part of a larger methodology to help marketers assess the value of a Customer Data Platform and plan for deployment. I expect to be describing the full approach over the next couple of months...stay tuned for details.
______________________________________________________________________________________
*a name that virtually demands a sidekick. Obvious choice is “Data Boy” but I’m sure my readers can think of something more clever.
† and appreciate the credit has he given me.
** Yes, I do recognize how fortunate I am that this is of my major problems in life.
†† Not really. The snake dream is how KekulĂ© discovered the structure of benzene. But it makes a good story, eh?
I’m delighted that Scott has found the CDP concept useful† and am in turn happy to adopt his distinction between Backbone Platforms and the other types of marketing applications. The Backbone Platforms are, indeed, platforms that support most Experience and Operations systems, enabling those systems to focus on particular tasks without creating complete customer management environments of their own. That's a difference worth noting.
Scott never claimed that his diagram illustrates a precise relationship among the components, so it's no criticism to point out that it doesn't. Experience and Operations systems sometimes connect with Backbone Platforms through a Middleware system, but more often they connect with the Backbone Platforms directly. In fact, some of the Experience and Operations systems connect with multiple Platforms, serving as sort of do-it-yourself Middleware. The challenge of illustrating this becomes clear when you try adding lines to show how the classes of systems interact with each other – it’s not as simple as connecting the adjacent layers on Scott’s diagram.
Being a visual thinker, I found this ambiguity to be endlessly disturbing.** Try as I might, I couldn’t rearrange the boxes to show the relationships correctly.
Then, I had a dream about a snake rolling downhill with its tail in its mouth, and discovered the answer: the systems could all be arranged in a circle graph, allowing any two to be connected directly.††
I must admit that I am ridiculously pleased with this approach. I know there’s nothing especially brilliant about circle graphs per se, but I’ve never seen one used in an architecture diagram. The pictures below illustrate, at least to my satisfaction, how much more clearly the circle graph shows relationships among systems than the traditional boxes and layers. Each diagram shows the same relationships among a small set of systems. The top left picture uses the traditional approach of showing only the links between categories – as you see, this hides any connections between non-adjacent components or individual systems. The top right picture shows the direct connections between systems, but it’s hard to read because lines cross behind the boxes. True, you could use curved lines to avoid this, but that quickly becomes impractical. The bottom picture shows the circle approach: here, the lines themselves might cross but no connections are hidden. The relative clarity of the circle graph grows as more systems are introduced.
Showing the actual connections between system pairs has another advantage: it lets you represent the architecture as a formal graph, meaning you can compare architectures using standard graph analysis techniques. Even just counting the connections gives a useful measure of relative complexity.
The diagrams below illustrate this nicely: the top picture shows the same architecture as before, which has 14 system-to-system connections (out of 28 possible pairs, another useful metric, even though some wouldn't make much sense). The bottom picture shows the same systems with everything connecting through a central database: now there are only eight connections and several missing system-to-system links have been provided automatically. If you want a crude approximation of how much a central database reduces complexity (and hence cost), this is good place to start.
The circle approach has other advantages, such as making it easier to see missing connections between systems. I'm working on it as part of a larger methodology to help marketers assess the value of a Customer Data Platform and plan for deployment. I expect to be describing the full approach over the next couple of months...stay tuned for details.
______________________________________________________________________________________
*a name that virtually demands a sidekick. Obvious choice is “Data Boy” but I’m sure my readers can think of something more clever.
† and appreciate the credit has he given me.
** Yes, I do recognize how fortunate I am that this is of my major problems in life.
†† Not really. The snake dream is how KekulĂ© discovered the structure of benzene. But it makes a good story, eh?
Monday, January 06, 2014
BrightInfo: Content Recommendations Made Simple
I spent much of last year writing about Customer Data Platform systems and have reviews on tap for a half dozen more. But I thought I’d start out 2014 with something different, just to show I’m not totally obsessed. Although, as you’ll see shortly, there’s a CDP angle to this story as well.
Today's topic is BrightInfo, which uses semantic technology to automatically recommend the most relevant content to Web site and blog visitors. Specifically, the system crawls the client’s Web site and blog to find and classify existing content, and then tracks visitor behavior to offer new content relevant to what the visitor has already selected. The recommendations can be presented on a fixed area of a page or as a pop-up. They can appear continuously or only when a visitor indicates they are about to leave by moving their mouse towards the browser’s URL bar. BrightInfo uses Javascript tags and cookies to track visitors over time, allowing it to base recommendations on individual behavior as well as content similarity and popularity. Behaviors across Web sites, landing pages, and blogs are all tracked by the same cookie, so each recommendation reflects a consolidated history. However, the system does not incorporate other information sources – meaning it can’t use the central customer data a CDP would provide. Nor, at present, does the system support mobile, which doesn't use cookies and requires different display methods. But this is coming soon.
It should be fairly easy for BrightInfo to access external data sources, since the necessary changes are unrelated to its core technologies of semantic analysis and recommendations. Most companies today could probably use the system as it stands, since they lack a centralized customer database or policies to coordinate customer treatments across channels. BrightInfo already lets users override the purely algorithmic recommendations by specifying that some content will be shown in all circumstances, that other content will never be shown, and that recommendations will appear only on specified pages. Sophisticated marketers might want more refined controls, such as limits on how often the same content is offered or recommendations based on expected response value rather than the simple click rate. But BrightInfo is targeted at small and mid-size businesses, which are less concerned with such refinements.
What those businesses do care about are easy deployment and low cost. BrightInfo provides those by automating the content discovery and classification, running as a service rather than installed software, and pricing based on visitor volume. Javascript tags, cookies, and isolation from other data sources also simplify deployment, whatever their other drawbacks. Measurement is similarly simplified by providing reports that compare how many clicks were made on native content and system-recommended content. Clicks on system-recommended content are a rough measure of system-added activity, although presumably some visitors would have chosen other content had the recommendations not been available. BrightInfo considered setting up formal a/b tests to measure true incremental value, but found that most small and mid-size businesses have too little volume to support this. The company has recently integrated its reporting with Marketo, HubSpot, and Google Analytics.
BrightInfo officially released its product last September, after about a year of development. The underlying semantic and recommendation technologies came from sister company Softlib Software, which uses them for automated service and knowledge management and was founded in 2004. Pricing is published on the BrightInfo Web site and is free up to 1,000 visitors per month, $89 per month up to 5,000 visitors, and $224 per month up to 15,000 visitors. The system has several dozen clients.
To summarize, then: BrightInfo provides a very simple, very low cost way to increase engagement with Web visitors by making targeted content recommendations. It's worth knowing about because traditional recommendation engines are often harder to deploy and more expensive.
But what’s the CDP angle? It’s not simply that BrightInfo is an example of an application that could use the customer data in a CDP to make more accurate recommendations. It’s actually a somewhat deeper question of where the recommendation functions belong in a CDP-based architecture. I’d argue that recommendations should be part of the central platform, so they can be used to coordinate treatments across all touchpoints. In other words, it’s probably wrong to imagine BrightInfo as an application that attaches to a CDP and uses its data to improve Web and blog results. Rather, in an ideal world, BrightInfo’s technology would be used within the CDP to generate recommendation that the CDP itself feeds to all applications. This is pretty theoretical and largely irrelevant to BrightInfo itself, which is targeted at companies that don’t have a CDP in the first place. But as marketing technology continues to evolve and more companies have CDPs, or centralized customer databases by any other name, it’s important to understand how the pieces should fit together.
Today's topic is BrightInfo, which uses semantic technology to automatically recommend the most relevant content to Web site and blog visitors. Specifically, the system crawls the client’s Web site and blog to find and classify existing content, and then tracks visitor behavior to offer new content relevant to what the visitor has already selected. The recommendations can be presented on a fixed area of a page or as a pop-up. They can appear continuously or only when a visitor indicates they are about to leave by moving their mouse towards the browser’s URL bar. BrightInfo uses Javascript tags and cookies to track visitors over time, allowing it to base recommendations on individual behavior as well as content similarity and popularity. Behaviors across Web sites, landing pages, and blogs are all tracked by the same cookie, so each recommendation reflects a consolidated history. However, the system does not incorporate other information sources – meaning it can’t use the central customer data a CDP would provide. Nor, at present, does the system support mobile, which doesn't use cookies and requires different display methods. But this is coming soon.
It should be fairly easy for BrightInfo to access external data sources, since the necessary changes are unrelated to its core technologies of semantic analysis and recommendations. Most companies today could probably use the system as it stands, since they lack a centralized customer database or policies to coordinate customer treatments across channels. BrightInfo already lets users override the purely algorithmic recommendations by specifying that some content will be shown in all circumstances, that other content will never be shown, and that recommendations will appear only on specified pages. Sophisticated marketers might want more refined controls, such as limits on how often the same content is offered or recommendations based on expected response value rather than the simple click rate. But BrightInfo is targeted at small and mid-size businesses, which are less concerned with such refinements.
What those businesses do care about are easy deployment and low cost. BrightInfo provides those by automating the content discovery and classification, running as a service rather than installed software, and pricing based on visitor volume. Javascript tags, cookies, and isolation from other data sources also simplify deployment, whatever their other drawbacks. Measurement is similarly simplified by providing reports that compare how many clicks were made on native content and system-recommended content. Clicks on system-recommended content are a rough measure of system-added activity, although presumably some visitors would have chosen other content had the recommendations not been available. BrightInfo considered setting up formal a/b tests to measure true incremental value, but found that most small and mid-size businesses have too little volume to support this. The company has recently integrated its reporting with Marketo, HubSpot, and Google Analytics.
BrightInfo officially released its product last September, after about a year of development. The underlying semantic and recommendation technologies came from sister company Softlib Software, which uses them for automated service and knowledge management and was founded in 2004. Pricing is published on the BrightInfo Web site and is free up to 1,000 visitors per month, $89 per month up to 5,000 visitors, and $224 per month up to 15,000 visitors. The system has several dozen clients.
To summarize, then: BrightInfo provides a very simple, very low cost way to increase engagement with Web visitors by making targeted content recommendations. It's worth knowing about because traditional recommendation engines are often harder to deploy and more expensive.
But what’s the CDP angle? It’s not simply that BrightInfo is an example of an application that could use the customer data in a CDP to make more accurate recommendations. It’s actually a somewhat deeper question of where the recommendation functions belong in a CDP-based architecture. I’d argue that recommendations should be part of the central platform, so they can be used to coordinate treatments across all touchpoints. In other words, it’s probably wrong to imagine BrightInfo as an application that attaches to a CDP and uses its data to improve Web and blog results. Rather, in an ideal world, BrightInfo’s technology would be used within the CDP to generate recommendation that the CDP itself feeds to all applications. This is pretty theoretical and largely irrelevant to BrightInfo itself, which is targeted at companies that don’t have a CDP in the first place. But as marketing technology continues to evolve and more companies have CDPs, or centralized customer databases by any other name, it’s important to understand how the pieces should fit together.