R E P O RT R E P R I N T
Conversion Logic aims to
outsmart previous attribution
platforms with multiple models
SCOT T DENNE
7 DEC, 2015
Just a few years into a movement to make multi-channel attribution a standard feature of marketing, Conversion Logic
has entered the fray with a strategy to combine different statistical approaches into a single method for properly crediting the impact of multiple marketing and advertising methods.
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Just a few years into a movement to make multi-channel attribution a standard feature of marketing, Conversion Logic has entered the fray with a strategy to combine different statistical approaches into a single method for properly crediting the impact of multiple marketing and advertising methods. It claims to have solved
some of the early technical challenges to broad adoption in this segment, and its early results validate the
appetite for newer products in this still-new segment. The most substantial obstacles to widespread adoption
that the company and its peers will face, however, are organizational rather than technical.
T H E 4 5 1 TA K E
Knowing what’s working and what’s not – what could make more sense for a marketer? That simple idea has
led to a growing amount of traction and experimentation in multi-touch marketing attribution, and a shift
away from last-click attribution. But simple ideas are often complex in their execution; this is certainly the
case in multi-touch attribution. Despite the challenges, the timing is ripe for multi-touch attribution. Multichannel marketing – the idea that marketing should be orchestrated around the customer, not the channel
or application – is gaining traction, and cross-channel attribution is needed to implement this strategy. Also,
more customer data and more integration points among different types of customer data are emerging,
making for a richer pool of data to build more accurate attribution models. Conversion Logic, with a flexible
technical offering, is well-positioned to benefit from these trends.
CONTEXT
The market for multi-touch attribution is still in its infancy; it has only begun to gain traction in the last three or four years.
Prior to this, most attribution systems were built around last-touch attribution, where all the credit for a conversion was
given to the most recent ad or marketing message to reach a customer before the conversion. Some slightly less simple
methods would spread the credit among the various ads based on preset rules, such as dividing the credit equally among
all ads or giving 80% to the two most recent and dividing 20% among the rest. The growth of Visual IQ, the founding of
Convertro and Adometry’s pivot away from click-fraud analysis earlier in this decade ushered in the use of algorithmic
modeling to determine the adds a customer likely saw and the weight that should be given to each.
Conversion Logic was founded in 2014 by CEO Trevor Testwuide and COO Alison Latimer Lohse, two former employees
of Visual IQ, with the goal of building an attribution platform that would have a shorter implementation time and more
flexibility in the statistical models. The Los Angeles-based company raised $4m in seed funding from Rincon Venture
Partners, Crosscut Ventures, Lerer Hippeau Ventures, TenOneTen, Founder Collective and Raptor Group. It currently has
20 employees. Its initial offering exited beta testing in June, and counts Guthy-Renker and The Children’s Place among its
initial 15 customers (targeting 40 by the end of 2016). Monthly contracts range from $10,000-20,000.
PRODUCTS
Multi-touch attribution systems collect data from across a company’s marketing efforts – from email, display, TV and so
on. Those are correlated to conversion data from a company’s website, point-of-sale system and other sources of conversion information to form a picture of individual customer journeys toward a conversion. The system will then model out
the unknown connections among the different channels and use different statistical models to assign credit to different
points on the journey.
The various attribution vendors differ in the level of data they collect and in the types of models they use. For example,
one vendor might note the publisher website where an ad ran, while another might also note the placement of the ad.
On the statistical models, many use linear regression, which assigns value to each interaction in a decreasing amount with
the time passing before conversion. Others use game theory, which analyzes the interplay between the different ads seen
leading up to a conversion.
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Rather than choosing a single model, Conversion Logic uses an ensemble model, which runs the data through
multiple models and combines the results from each separate statistical model, with more or less weight given to
each based on its validation against a previously validated sample. This enables marketers to use the models that
fit their marketing environment, and even to bring their own attribution models into the platform.
In addition to its multi-touch attribution, which measures both digital marketing and offline marketing channels,
such as radio and TV, Conversion Logic offers a product that applies the same technology to measuring the shortand long-term impact of direct-response advertising on television. For both products, its customers are mainly
direct-response advertisers.
S T R AT E G Y
The time it takes to deploy an attribution system has been a significant roadblock to many successful implementations. To start with, there’s a data-collection challenge – many different sources of media pricing, advertising reach
and customer-conversion data must be collected and aligned with the channel-specific data that the organization
already has. Then the models must be developed and refined in a recurring gather-model-test cycle.
Conversion Logic attempts to compress this process by architecting its system using methods borrowed from
programmatic advertising and real-time ad exchanges; much of its engineering team comes from Rubicon Project,
an ad exchange. That appears to be resonating – Conversion Logic claims that three-fourths of its customers have
previously deployed another multi-touch attribution vendor.
In addition to the right statistical models and nailing the implementation, a successful attribution deployment
project also needs the cooperation and confidence of the entire marketing team. That’s tough to get in many
organizations, and no amount of technical tweaks can push past it. At the strategic level, a working attribution
program has clear benefits for media planning and optimization; less so at the tactical level. Once an attribution
platform is in place, the different teams suddenly have their success judged with a different set of metrics. The
search marketing team, for example, might be told that it’s most effective when drafting on a display campaign,
and therefore some of its budget is shifting to the display team. It’s likely that the search team will have its own
metrics to dispute that.
COMPETITION
Most of the first generation of multi-touch attribution vendors have been acquired recently. This has had a substantial impact on the market, and offers both opportunities and challenges to Conversion Logic. Two of its
competitors – Adometry (Google) and Convertro (AOL) – are now owned by media companies. That has raised
questions about the neutrality of those tools, given the core business of the parent companies, and provides an
opening for new entrants. The problem, however, is that AOL and Google can (and do) offer free and inexpensive
attribution as part of a media package – an incentive that Conversion Logic cannot match.
Visual IQ is the remaining independent from the first generation of companies. It is also the largest independent
company in this space, and has far greater name recognition in this segment than Conversion Logic or any of the
other emerging companies, including Abakus and C3 Metrics.
Conversion Logic also competes with MarketShare, which was recently acquired by marketing data service provider Neustar. MarketShare built a media mix modeling business, and has added attribution capabilities in recent
years. Those capabilities were developed in-house and through its recent acquisition of DataSong.
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RECENT ADV ERTISING ATTR IBUT IO N A N D A N A LY T ICS ACQ U ISIT IO N S
Date announced
November 5, 2015
April 1, 2015
May 6, 2014
May 6, 2014
Target
MarketShare
DataSong
Adometry
Convertro
Acquirer
Neustar
MarketShare
Google
AOL
Deal value
$450m
undisclosed
$150m*
$89m
Revenue
$57m
$3.5m*
$20m*
$11m*
Source: The 451 M&A KnowledgeBase
*451 Research estimate
SWOT A NA LYS I S
ST R E N GT H S
Conversion Logic enables marketers to combine multiple statistical models to arrive at a
custom attribution model for their business.
WEAKNESSES
The company is less than two years old, and
its competitors have far greater recognition
and other media assets to entice marketers
onto their attribution platforms.
O P P O RT U N I T I E S
The timing is right for multi-touch attribution. Multi-channel marketing is gaining traction, and cross-channel attribution is needed
to implement this strategy.
T H R E ATS
A successful attribution deployment needs
the cooperation and confidence of an entire
marketing team. In many organizations that’s
tough to get, and no amount of technical
tweaks can push past it.