Drowning in data uh? Pretty scary right?. We know how it feels. That’s why we developed a set of end to end solutions focused on providing you with the decision making models so you only need to focus on the important, making decisions that impacts in your company’s bottom line.
- Cohort Analysis: Cohort analysis is a subset of behavioral analytics that takes the data from a given eCommerce platform, web application, or online game and rather than looking at all users as one unit, it breaks them into related groups for analysis. These related groups, or cohorts, usually share common characteristics or experiences within a defined timespan. Cohort analysis allows a company to “see patterns clearly across the lifecycle of a customer (or user), rather than slicing across all customers blindly without accounting for the natural cycle that a customer undergoes.” By seeing these patterns of time, a company can adapt and tailor its service to those specific cohorts.
- A/B and multivariate testing at a massive scale: Multivariate testing is a process by which more than one component of point of contant between the company and the client (Website, APP, Advertising Campaign) may be tested in a live environment to identify which one performs best in terms of conversions (sales, registrations, etc). It can be thought of in simple terms as numerous A/B tests performed on one page at the same time. A/B tests are normally used to determine the better of two content variations while multivariate testing can theoretically test the effectiveness of limitless combinations. The only limits on the number of combinations and the number of variables in a multivariate test are the amount of time it will take to get a statistically valid sample of visitors and computational power.
- Conjoint Analysis: Conjoint analysis is a statistical technique used in market research to determine how people value different attributes (feature, function, benefits) that make up an individual product or service.The objective of conjoint analysis is to determine what combination of a limited number of attributes is most influential on respondent choice or decision making. A controlled set of potential products or services is shown to respondents and by analyzing how they make preferences between these products, the implicit valuation of the individual elements making up the product or service can be determined. These implicit valuations (utilities or part-worths) can be used to create market models that estimate market share, revenue and even profitability of new designs.
- Ad-hoc Attribution Models: Attribution models are not based on how likely is each channel on generating a conversions but on whimsical definitions that has little or nothing to do with the reality. So depending on the attribution model you chose you impact one positively or negatively each of the inbound traffic channels. That’s why at Intellignos we developed a proprietary model to generate an ad-hoc algorithm that attributes conversions (costs, income, etc) based on real data.
- Predictive Analytics Modelling: We use data series from past actions, like campaigns or customer purchasing behaviour data series, along with a set of common accepted statistic models to predict future outcomes. If you have questions like “What will happen if I invest 20% more in channel A?”. How will be the reaction of Cluster A towards a the Action X? then Predictive Analytics Modelling is the answer.
- Big data environment design, implementation and configuration: One of the biggest fears any manager can face today is being ask to design and implement the Big Data Environment. A minimum mistake or deviation can became a never ending story becoming the cliché of the money pit. We count with the experience to make your Big Data implementation a headache free turn key solution.
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