Marketers want insights into what triggers consumers to purchase, how they make a purchase decision, how they decide where and when to purchase, and even how they use the products they purchase. Data Mining AnalyticsIDP delivers data-driven marketing solutions targeted to these directives. And focused on the art & science of ‘invasive’ data management and deep-dive data mining.

For 2018, businesses will focus more of their attention into data. They have already seen the importance of data mining so more and more businesses will invest to that. — CustomerThink, Dec 2017

Data Mining Analytics — Challenges

Effective use of customer data is a competitive weapon. And marketers rely heavily on specific-purpose data mining analytics. And yet, marketers fail to get deep-dive analytics. They’re swamped by the volume and velocity of data; and stymied by the lack of internal data management skills. It’s also true that many marketers aren’t sure of the data they do have; they don’t believe they have the data they need; and what they have, they question the quality — or they can’t access.

The roadblock isn’t statistics, but efforts needed to integrate data into actionable data sets used to generate analytics.

Retailers don’t have a good track record for deriving insights from data they hold — even when that data was only purchase history, tracked through loyalty programs. If you think retailers are going to magically start getting business-altering insights out of connecting social media data to consumer behavior any time soon, you will be sorely disappointed. — Forbes, Oct 2015

In-house reporting tools simply don’t deliver. And business analysts don’t engage in data mining due to a lack of data management skills. Analysts might be Excel wizards, but most aren’t trained in deep-dive data mining; they can’t manage complex data structures, or disparate data sources. For many analysts it’s just too much ‘data janitor work’. They don’t want their time mired in collecting and preparing data. So analysts create incomplete, inappropriate and error-filled reports. Marketers don’t get the complete customer picture, and lose confidence in both analytics and data.

Companies are increasingly viewing data as a competitive advantage. The Ubers and Airbnb’s of tech have mastered using data to build better and smarter technology products. Now other tech companies are looking to do the same, and this is causing a major talent shortage.– BusinessSoluntions, Sept 2016

Data Mining Analytics — IDP

Data Mining Analytics
At IDP we know your data is challenging, out of reach, or too complex for your business analyst. And that you have limited resources.

Far too much handcrafted work — what data scientists call ‘data wrangling’, ‘data munging’ and ‘data janitor work’ — is required. Data scientists spend from 50% to 80% of their time mired in this mundane labor of collecting and preparing unruly data. — NYT, Aug 2014.

We remove the requirement that business analysts manage large data volumes or complex data structures — bridging the gap between data management and analytics — so business analysts focus, not on data, but on making recommendations from analytics. We expertly manage large data volumes with complex structures and integrate disparate data sources to build rock-solid analytical data sets, even when facing difficult data. And we always collaborate with marketing to generate the right methodologies that produce actionable results.

When the source data is rock-solid, Data Mining Analytics become much, much easier!