- Category: December 2015 - Omnichannel Marketing
Marketing is in flux these days, as a variety of new channels and tactics have to be united in an integrated customer-centric approach to succeed. What comes increasingly to the fore, due to the complex marketing environment and the transition from single-channel to omni-channel strategies, is that a meaningful solution to measure success is needed, which can represent the customer journey at large and the related effects on the conversion or branding objectives.
Given rapid developments and diversification, the oversupply of evaluation tools can be overwhelming. The circulating buzzwords, like game theory, dynamic attribution, or real-time modeling are for sure a memory hook, but may obscure the view on the essentials and lead to hasty decisions. Instead, it is important to formulate the own requirements first and only then to take a critical look at the offered solutions and methodologies.
So, what are the questions you should ask in order to be able to distinguish the true potential of an evaluation solution of false promises? How do you know you are selecting the one that can really help your marketing activities to succeed? Consider the following:
Does the provider understand the fundamental differences of the customer journey?
The ‘customer journey’ consists of a different length sequence of advertising contacts connected to one or more measurable customer activities: For example, a customer watches a TV spot, is doing research online and looks at display ads, until he finally converts online.
Well, although the influence of media can be relatively easily measured at the user level for all digital channels, for the offline channels, still no comprehensive user allocation can take place, because nobody knows the people who see a TV commercial. These fundamental differences in the availability of data requires the application of regression-based methods for omnichannel data and probabilistic or deterministic methods for digital data.
Does the methodology really leverage all available data points?
When choosing a marketing attribution solution, special attention should be paid to the fact that actually all media touchpoints are considered - from all channels and platforms at every stage of the customer journey. The use of probabilistic methods to digital data, e.g. game theories, result in inaccuracies of the contribution value, particularly with low data volume. Deterministic methods, however, calculate valid detailed statements on the distribution of fractional success of any particular media touchpoint and lead to more accurate results. Regression-based methods are the most common approach for omnichannel models, due to the lack of granularity which is compensated mostly by using longer time series.
Has the solution proven its worth in terms of ROI?
Before choosing a solution, the provider should be able to show references from existing customers and clearly prove how the solution has made an impact on the ROI. Moreover, it should be thoroughly researched whether the methodology in question has been extensively tested by independent analysts.
Do the results surpass the expectations?
Marketing attribution solutions must have scientific and mathematical methodologies as a basis that are continuously checkable and verifiable. Thus, providers are able to reliably predict how high the improvements in media efficiency are – or consequently fail in achieving increased ROI. Well, the actual market results must at least comply with these forecasts.
Does the considered solution already reach product maturity?
Some marketing attribution solutions have already reached the level of maturity without continuous adjustments to create added value for companies. In practice, product providers should answer questions such as: What is the data integration process? How does the product require the data? Are there any specifications? Is there an admin console? How many of my requirements can I implement directly in the user interface? How many version changes have taken place and are all clients on the same version? Is there an online help? Watch out for providers with a great PowerPoint, instead of product approach who allures with most individuality, hides the facts of higher overall costs and longer integration times.
Is there a clear distinction between correlation and causality?
In marketing, correlation is very often mistaken for causality, hence, the more important it is to differentiate very clearly between these two concepts within a marketing attribution methodology. Correlation indicates the strength and direction of the relationship between two variables, but can be quite random in nature, whereby the change of a variable does not affect the other. A causality, however, describes a proven relationship of cause and effect, in which the change of a variable has a direct impact on the other. Correlation does not imply causality and can never be based on an assessment of marketing success. A good example of correlation is the frequently used practice of attributing TV advertising to digital data, but there is no causality that a certain spot leads to a higher number of conversions an hour after the broadcast.
Can the method be tailored to unique business objectives?
Prerequisite for selecting a suitable performance measurement solution is an accurate knowledge of your own individual business objectives, KPIs, classifications, costs and business rules. This ensures that the methodology can be integrated into the corporate daily routines and the gained insights and recommendations are relevant and usable. Not all marketing attribution solutions have the flexibility to adapt to specific business needs.
Is the activation part of the solution?
By nature, the focus of a marketing attribution solution is on accurate measurement and optimization, but when improving the marketing power, the activation of the results plays an equally important role.
A solution that can utilize immediately the gained insights, via direct transfer to programmatic execution platforms, ensures that the media placements are always based on the latest and most accurate data.
If a proper handling is provided, the marketing attribution can give valuable and directly usable insights for the precise budget allocation and improve your marketing performance.
So, instead of risking to be blinded by melodious promises, you should ask the solution providers the right questions. Only that way can you find the ideal solution in the form of a proven methodology that pulls all the data points up, differentiates between causality and correlation, and delivers through its configuration the maximum ROI, according to your individual needs.
By Daniela La Marca