Visual IQ Measures Impact of Online Campaigns

Visual IQ promises to “solve your dilemma of capturing, integrating, analyzing and understanding your marketing performance data.” Word choice aside*, this promises exactly what I want from a marketing measurement system. Within limits, Visual IQ appears to deliver.

First a bit of background. Visual IQ is the name adopted in February 2008 by Connexion.a, a firm founded in 2005 with roots in online marketing measurement. The goal was (and is) to help marketers do a better job of allocating their budgets by comparing results across channels. The particular focus has been digital channels—display ads, paid search, organic search, affiliate programs, mobile, etc.—although the company can analyze data from conventional channels as well. The core technology is an “Online Intelligence Platform” that integrates data from all sources and presents it in a way that shows the value of each campaign. This happens in three system modules, each representing a higher level of sophistication.

• IQ Reporter accepts campaign-level inputs and presents campaign-level results. These can be from one or multiple channels and incorporate plan, actual and syndicated competitive information. The value is being able to view data from different sources and multiple channels in a single reporting system. Visual IQ has developed some attractive tools for reporting and analysis. Technically these are quite impressive, using Adobe Flex technology to deliver rich interactive analytics through a browser.

• IQ Envoy steps up to individual-level data from cookies, transactions and other sources. It consolidates this by customer to view contacts across campaigns. Since individual-level data involves much more volume than campaign statistics, Visual IQ extracts selected attributes from each channel’s inputs and loading them into a proprietary database. This compresses the data for storage and decompresses it for analysis. The system can automatically poll for new data on what the company calls a “near real time” basis, which is usually daily but can be more often if appropriate. The attributes extracted for each channel are defined in a standard data model, which makes it easier to set up new clients and add new channels to existing clients.
  
  Managing data at the customer level lets the system look across campaigns to find all contacts leading up to an interaction such as a purchase. This lets Visual IQ apply statistical methods to estimate the contribution that each contact made to the final result. These models can look across contact attributes, such as campaigns, web sites, keywords, creative treatments, and dates, to better understand the exact elements that are driving response. Such information lets marketers allocate funds to the most effective treatments--a major step towards true marketing optimization.
  
  The challenge here is the scope of information available to analyze. Visual IQ relies primarily on ad server cookies to track the messages received by each individual. This automatically creates a history of ads served by the ad network itself. But it requires additional coordination for the ad server to track organic search, paid search and affiliate campaigns. Information other channels, both online and offline, requires additional identifiers. Typically it would depend on establishing the actual user identity at the time of a transaction, and then linking this to identifiers in other channels. For example, an online purchase might capture an email address that could be linked to an email account, and capture an actual name and postal address that could be linked to a mailing list or regional media market. Exactly how much information will be available will depend on the situation and has little to do with Visual IQ itself. (Of course, you could argue that having Visual IQ available to analyze the data gives marketers a stronger reason to take the effort to gather it.)
  
  Just to be clear: cookies are inherently anonymous. Tying them to individuals requires information from an external source. Visual IQ can effectively analyze contact history of a given cookie without knowing the identity of its owner.

• IQ Sage uses the individual information to build customer profiles and to model the paths followed by customers as they head towards a purchase. These models can simulate the impact of changes in marketing programs, such as increasing spending on programs to move customers from one stage of the purchase cycle to the next, or switching funds to programs that attract different types of customers. Optimization can recommend changes that would produce the best over-all results.

Visual IQ offers its products as a hosted service with monthly fees ranging from $7,500 to $25,000. Cost depends largely on which components are used, with some additional fees for data storage. The company may adopt volume-based pricing in the future. Visual IQ has 14 clients, including very large advertisers, agencies and Web publishers. Although a majority of its clients use the system only for campaign-level reporting, about one-third work with cookie-level data.

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*The primary definition of “dilemma” is “a situation requiring a choice between equally undesirable alternatives.” (Dictionary.com) I don’t think that really applies here. Presumably Visual IQ has in mind the secondary meaning of “any difficult or perplexing situation or problem.”

MPM System Checklist

I’m planning a series of posts to review individual MPM reporting systems. Before doing that, it will help to set a framework of items to consider. I may expand this over time.

Inputs:

• treatments given to individual customers across all channels (this refers primarily to marketing messages, but could also include operational messages such as bills and service interactions)


• customer behavior history (purchases, refunds, service requests, etc.; this includes costs and revenues)


• customer attributes (demographics, location, needs, etc.; these should be standardized and grouped into audience segments to make analysis easier)


• treatment attributes (campaigns, products offered, pricing, positioning, media cost, etc. These should also be standardized and aggregated for analysis.)


• external conditions (competitive advertising and promotions, economic conditions, weather, etc.)

Processes:

• customer data integration (to associate all information related to individual customers. This is the clichéd 360 degree view.)


• response attribution (to measure the influence of each treatment on subsequent customer behavior. This a complex analytical process if done in depth; otherwise, it can be as simple – and simplistic – as directly matching responses to promotions.)


• brand value attribution (to measure the influence of each treatment on brand value. This is an unholy marriage of two frighteningly obscure methodologies: response attribution with brand value measurement.)


• predictive modeling and optimization (to recommend treatments during interactions and for outbound campaigns. This would also recommend optimized spending levels across channels based on business objectives and constraints.)


• lifetime value calculations. (These include projections for audience segments and estimated incremental lifetime value impact of specific treatments.)

Outputs:

• campaign reports (Basic information includes quantities, costs, and responses. Financial information includes return on investment, cash flow and profits by period. The financial results are based on response attribution. Depending on how attribution is handled, reports may show only direct effects or show direct effects plus long-term impacts.)


• treatment reports (Basic information shows how often different treatments are delivered. Advanced information shows the impact of treatments and treatment attributes on campaign response, customer value and brand value. Like campaign reports, treatment reports are based largely on response attribution.)


• customer reports (Basic information includes segment counts, demographic profiles and behavior profiles. Trends show changes in segments and migration of customers among segments. Customer reports also includes levels and changes in lifetime value.)


• Brand value reports (These show current brand value and changes in brand value. They report both aggregate values and details for brand value components.)

Key considerations within each of these topics include:

• the scope of data included (for example, which channels)


• degree of detail (or “granularity” if you want to impress someone. For example is customer information reported for individuals, audience segments or campaigns? What is the level of financial detail?)


• data latency (how long does it take before new data becomes available to the system?)


• implementation effort (time, skill levels, flexibility)

In addition, there are the standard considerations for any system:

• delivery model (hosted vs. on-premise)


• technical skills required to deploy and maintain


• end-user skills required to benefit from the system


• costs (hardware, software and services; implementation vs. on-going operation)


• scalability (relative to your own data volumes and user counts)


• vendor experience and stability


• technologies used (databases, .NET vs. J2EE, ‘fat client’ vs. browser-based, etc.)

A word of caution: any list like this favors products with many features, even though some of those features may not be poorly implemented. I consider MPM systems to be in an early stage of development, which means there will be a variety of specialist products (a.k.a. “point solutions” or “best of breed”) that do just a few things but do them very well. This will change over time as requirements for different functions become better understood and standard practices emerge. For now, it’s probably more important to make sure any give product meets your critical needs than to try to find a one-size-fits-all solution that does everything. It’s a safe bet that the major platform vendors (of enterprise systems like SAP or Oracle, or marketing systems like Unica, Aprimo, SAS or Teradata) will eventually provide comprehensive solutions, so anything you buy now will only last a few years at best.

MPM Reporting Software

One of my intentions for this blog is to help you find vendors for MPM projects. Let’s jump right in with software providers specializing in MPM systems. There are just a handful of these once you narrow the focus to firms that are:

• primarily software developers rather than consultancies (although all vendors provide some consulting to help you set up and use their products, and a couple of consultancies have slipped into the list below if I think their software can stand on its own)


• dedicated primarily to analyzing marketing results (as opposed to generic reporting systems or broader marketing management systems)


• work across multiple channels (as opposed to a single channel such as Web analytics or paid search management).

My current list is below, in alphabetical order. I plan to update this over time and welcome suggestions for additions. Each vendor is listed with a brief description taken from their Web site. I will post links to detailed reviews of individual vendors as I write them.

DecisionPower

• My take: builds simulations using ‘agent-based modeling’, a specialized approach that is very powerful and efficient. These can be used to create the equivalent of a traditional marketing mix model.


• Company quote: “The cornerstone of DecisionPower™ products and services is agent-based modeling (ABM) technology. ABM gives you the power to simulate real-life consumer behavior in real-world markets — in real time.”

• My review (from 2006)

Decisions Made Easy (Nielsen)

• My take: provides tools to build and analyze databases of point-of-sale and syndicated data.


• Company quote: “Decisions Made Easy, a global business service of The Nielsen Company, provides software and services for consumer goods manufacturers and retailers focusing on direct data. Clients use our solutions to efficiently extract insight from point-of-sale (POS) and related data, and create actionable information for use across the business.

Factor TG Leading Brands

• My take: analyzes program results based on online consumer surveys. A limited but interesting approach.


• Company quote: “Leading Brands provides a system of continuous marketing measurement that captures the effects of specific marketing tactics as they happen via online consumer surveys. Brand effects are measured according to accepted research methods, analyzed with sales data, and reported when and how you need them (for planning, execution, optimization, and modeling.)”

• My review (May 2008)

HardMetrics

• My take: not MPM specialists, they have a flexible technology for cross-system process measurement which was originally for call center performance management.


• Company quote: “MPM takes a self-service approach that allows you to define, drill and analyze in real time, your own dashboards, scorecards, reports and alerts on any moving part of a campaign. What’s even better is MPM allows you to drill down/up/sideways into any data source, anywhere in the enterprise to get the answers you need. ... HardMetrics is the industry’s FIRST and ONLY performance management company to offer a “codeless implementation’. That means your marketing organization can have a production ready system in hours/days and not have to wait weeks/months.”

• My review (June 2008)

Marketing Management Analytics Avista DSS

• My take: they’re really a consultancy with roots in marketing mix models, but they’ve productized their offering in Avista.


• Company quote: “Avista Decision Support Service provides marketers with an easy-to-use toolset that delivers on-demand insights about the effectiveness of marketing efforts. It combines the insights from MMA marketing mix models with the real time analytic power of industry-leading business intelligence to support fact-driven decisions – all drawn from a company’s integrated marketing data.... On-demand analytic tools support “what-if” scenarios, optimization, forecasting, portfolio allocation and media schedule optimization. Avista management dashboards support continuous tracking and diagnosis of marketing performance to help companies generate the maximum return from their marketing investment.”

• My Review (July 2008)

M-Factor M3

• My take: system combines modeling, planning and comparisons against actuals; can use models developed by the vendor or elsewhere.


• Company quote: “M-Factor provides marketing investment management solutions that keep analysis up to date and reveal choices with the best bottom-line results. Components include: Specialized reports that explain results as they occur; Scenario builder that predicts P&L impact from plan changes at any product and market level; Optimization engine that runs thousands of simulations within business constraints to maximize desired outcomes.”

• My review (June 2008)

Revcube

• My take: real-time reporting and optimization, online channels only. [4/24/08 - The company tells me they are repositioning to specialize in identifying optimal landing pages for customer segments. Formal launch is expected in the 3rd quarter of 2008.]


• Company quote: “Our proprietary platform captures and processes all useful data in the customer acquisition cycle across every online media channel. Proprietary algorithms then use this response data to generate optimization rules which are applied to campaigns in real-time. Optimization of placement, creative and budget occurs both within a single channel as well as across multiple channels including paid search, contextual search, display and email. This complete solution provides real-time attribute level reporting giving the advertiser unprecedented insight and control of their marketing efforts.”

• My review (June 2008)

SAS Marketing Performance Management

• My take: a comprehensive performance analysis and simulation system; SAS calls it MRM because it has another product called MPM which is more straight reporting.


• Company quote: “MRM automatically links sales and other business results to the marketing investments that drive them....With SAS, it is now possible to continuously plan, measure and optimize the impact of marketing spend on revenue and profitability.”

• My review (May 2008)

Upper Quadrant UQube

• My take: they consolidate media plans and sales results and make the results available with some forecasting and analysis tools. But no marketing mix models here.


• Company quote: “UQube Marketing is comprised of a series of web-based applications that automatically consolidate and interlink all marketing campaign schedules and sales data from any source. Each UQube Marketing application provides Cross Channel Reporting and Dashboards, Forecasting and Analytics, and rules based, version controlled Media Plan Management. Applications can be purchased separately or fully integrated with one another, and with the UQube Call Center Application Suite.”


• My review (from 2005)

Viewmark Viewmetrix

• My take: primarily an e-marketing consultancy but offers a powerful system to consolidate and report on marketing data across channels.


• Company quote: “Our Viewmetrix marketing-intelligence tool is an award-winning solution that lets you capture and correlate information from many sources – both online and offline. You can then analyze and present that information so you will make good business decisions now and secure new program resources for the future.”

• My review (June 2008)

VisualIQ

• My take: gathers customer-level data from online media and transactions, produces detailed analysis of factors influencing customer behavior.


• Company quote: “Visual IQ is one of the few marketing intelligence solutions capable of normalizing and integrating syndicated data, planning data and actual results from your campaigns - across multiple disparate data sources....[IQ] Reporter provides agencies and marketers the full data capture, integration, basic analysis and accurate reporting you need to make informed decisions and investment. IQ Envoy combines all of the features of Reporter with sophisticated media channel intelligence, customer transaction data, and high definition cookie-level analysis. Intuitive, customizable dashboards present intelligence in the formats most useful to your team. IQ Sage takes customer intelligence to its highest levels through the use of predictive modeling, scenario building, and simulation.”


• My review (April 2008)

Hello, World!

This blog will provide hands-on advice on building systems to gather, analyze and deploy marketing performance information. I hope you find it helpful.