My rational brain knows that there’s probably no reason for this flurry of sightings beyond pure coincidence. But it’s human to see patterns where they don’t exist, so I did find myself wondering if attribution is becoming a hot topic. I can easily come up with a good story to explain it: marketing technology has reached a new maturity stage where the data needed for good attribution is now readily available, the cost of processing that data has fallen far enough to make it practical, and the need has reached a tipping point as the complexity of marketing has grown. So, clearly, 2016 will be The Year of Attribution (as Anna Bager and Joe Laszlo of the Internet Advertising Bureau have already suggested).
Or not. Sometimes random is just random. But now that this is on my mind, I've taken a look at the larger attribution landscape. Quick searches for "attribution" on G2 Crowd and TrustRadius turned up lists of 29 and 17 vendors, respectively – neither including Brightfunnel or Claritix, incidentally. A closer look found that 13 appeared on both sites, that each site listed several relevant vendors that the other missed, and that both sites listed multiple vendors that were not really relevant. For what it's worth, eight vendors of the 13 vendors listed on both sites were all bona fide attribution systems -- which I loosely define to mean they assign fractions of revenue to different marketing campaigns. I wouldn't draw any grand conclusions from the differences in coverage on G2 Crowd and TrustRadius, except to offer the obvious advice to check both (and probably some of the other review sites or vendor landscapes) to assemble a reasonably complete set of options.
I've presented the vendors listed in the two review sites below, grouping them based on which site included them and whether I qualified them as relevant to a quest for an attribution vendor. I've also added a few notes based on the closer look I took at each system in order to classify it. The main questions I asked were:
- Does the system capture individual-level data, not just results by channel or campaign? You need the individual data to know who saw which messages and who ended up making a purchase. Those are the raw inputs needed for any attempt at estimating the impact of individual messages on the final result.
- Does the system capture offline as well as online messages? You need both to understand all influences on results. This question disqualified a few vendors that look only at online interactions. In practice, most vendors can incorporate whatever data you provide them, so if you have offline data, they can use it. TV is a special case because marketers don't usually know whether a specific individual saw a particular TV message, so TV is incorporated into attribution models using more general correlations.
- How does the vendor do the attribution calculations? Nearly all the vendors use what I've labeled an "algorithmic" approach, meaning they perform some sort of statistical analysis to estimate the attributed values. The main alternative is a "fractional" method that applies user-assigned weights, typically based on position in the buying sequence and/or the channel that delivered the message. The algorithmic approach is certainly preferred by most marketers, since it is based in actual data rather than marketers' (often inaccurate) assumptions. But algorithmic methods need a lot of data, so B2B marketers often use fractional methods as a more practical alternative. It's no accident that the only B2B specialist listed here, Bizible, is the only company that uses a fractional method, as do B2B specialists BrightFunnel and Claritix. It's also important to note that the technical details of the algorithmic methods differ greatly from vendor to vendor, and of course each vendor is convinced that their method is by far the best approach.
- Does the vendor provide marketing mix models? These resemble attribution except they work at the channel level and are not based on individual data. Classic marketing mix models instead look at promotion expense by channel by market (usually a geographic region, sometimes a demographic or other segment) and find correlations over time between spending levels and sales. Although mix models and algorithmic attribution use different techniques and data, several vendors do both and have connected them in some fashion.
- Does the vendor create optimal media plans? I'm defining these broadly to include any type of recommendation that uses the attribution model to suggest how users should reallocate their marketing spend at the channel or campaign level. Systems may do this at different levels of detail, with different levels of sophistication in the optimization, and with different degrees of integration to media buying systems.
G2 Crowd and TrustRadius
- Abakus: individual data; online and offline; algorithmic; optimal media plans
- Bizible: individual data; online and offline; fractional; merges marketing automation plus CRM data; B2B
- C3 Metrics: individual data; online and TV; algorithmic; optimal media plans
- Conversion Logic: individual data; online and TV; algorithmic;optimal media plans
- Convertro: individual data; online and offline; algorithmic; mix model; optimal media plans; owned by AOL
- MarketShare DecisionCloud: individual data; online and offline; algorithmic; mix models; optimal media plans; owned by Neustar
- Rakuten Attribution: individual data; online only; algorithmic; optimal media plans; formerly DC Storm, acquired by Rakuten marketing services agency in 2014
- Visual IQ: individual data; online and offline; algorithmic; optimal media plans
- BlackInk: individual data; online and offline; algorithmic; provides customer, marketing & sales analytics
- Kvantum Inc.: individual data; online and offline; algorithmic; mix models; optimal media plans
- Marketing Evolution: individual data; online and offline; algorithmic; mix model; optimal media plans
- OptimaHub MediaAttribution individual data; online and offline; attribution method not clear; data analytics agency with tag management, data collection, and analytics solutions
- Adometry: individual data; online and offline; algorithmic; mix models; optimal media plans; owned by Google
- ThinkVine: individual data; online and offline; algorithmic; mix models; optimal media plans; uses agent-based and other models
- Optimine: individual data; online and offline; algorithmic; optimal media plans
G2 Crowd and TrustRadius
- AdGear Advertiser: full stack advertising platform inc. ad serving, bidding, exchange technology
- DialogTech: tracks inbound phone calls
- Google Analytics Premium: ad data analytics including algorithmic attribution
- Invoca tracks inbound phone calls
- Telmetrics: tracks inbound phone calls
G2 Crowd only
- Adinton: Adwords bid optimization and attribution; uses Google Analytics for fractional attribution
- Blueshift Labs: real-time segmentation and content recommendations; individual data but apparently no attribution
- IBM Digital Analytics Impression Attribution: individual data; online only; shows influence (not clear has fractional or algorithmic attribution); based on Coremetrics
- LIVE: for clients of WPP group; does algorithmic attribution and optimization
- Marchex: tracks inbound phone calls
- Pathmatics: digital ad intelligence; apparently no attribution
- Sizmek: online ad management; provides attribution through alliance with Abakus
- Sparkfly: retail specialist; individual data; focus on connecting digital and POS data; campaign-level attribution but apparently not fractional or algorithmic
- Sylvan: financial services software; no marketing attribution
- TagCommander: tag managemenet system; real-time marketing hub with individual profiles and cross-channel data; custom fractional attribution formulas
- TradeTracker: affiliate marketing network
- Zeta Interative ZX: digital marketing agency offering DMP, database, engagement and related attribution; mix of tech and services