Using a bottom-up model to guide your analysis, you can gather amazing insights from the data you already possess
The key to data analytics lies in asking the right questions, but success can often hinge on the person who is asking those questions.
Traditionally, organizations have analyzed their businesses from the perspective of the boardroom, approaching problems from the top down. But in trying to address how to best use their data to solve problems without first understanding the data itself, errors of human bias and oversimplification of the issue may occur. Consequently, company leaders may invest time, money, and resources into technology and products that don’t deliver on expectations. Just because a software package comes with a flashy dashboard and a colorful knack for highlighting correlated relationships doesn’t mean it’s all that great at proving the causal ones.
But there’s no turning…
Predict what your email database will do to improve your click rate
The growth in Data Science techniques during the last few years has generated a vast interest in using analytical techniques to optimise engagement on email campaigns. Whether a company wishes to compare the performance of two email templates, compare the performance of multiple email templates or see the association between several characteristics of an email and a single metric, Predictive Analytical techniques allow them to acquire the answers they need.
Below we are going to outline 3 techniques you can implement from ‘getting started’ lists of around 500 subscribers, to highly advanced models geared towards enterprise users.
Understanding Sample Size
For these techniques to make sense, it is important to have a basic understanding of statistical significance and what size of list may be required for your tests to be useful. Very basically, the larger the sample size, the more statistically significant…
Use predictive modeling to give your campaigns an edge over competitors
The Search Engine Marketing Professional Organization’s 2015 State of Search Industry Report provides several valuable insights derived from both marketer and agency practices over the past year. The most useful conclusions center on three forms of advertising: paid search, social media, and display media.
In general, marketers were more confident in managing paid search advertising efforts in-house, whereas social media advertising was a responsibility better left to outside agencies. This shows how marketers are often more comfortable managing “tried-and-true” tactics as opposed to navigating the more complex and fast-paced landscape of social media advertising.
Throughout the report, a continuous theme emerges regarding success in measuring return on investment. For a paid search campaign, it’s a relatively easy task because the data and tools used to properly interpret those data are…
Using predictive analytics effectively will allow you to increase sales, but only if you have right data
Applying predictive analytics to marketing campaigns will enable businesses to increase sales and returns through visualising the campaign outcomes. Below is an introduction to Predictive Marketing and how you can begin to experiment with these ideas in your business.
You may have heard of predictive marketing – it’s an increasingly popular topic. You may not, however, understand what it really means or how it could benefit your business.
In short: it involves using expected future events and expected future customer behaviours to create a marketing plan. It has become a lot more relevant to businesses as digital marketing campaigns have generated far more data which is analysed in far more detailed ways.
Intuitively, most marketers can see a clear value from understanding customers better and getting detailed numbers around a campaign’s expected returns before it has started.
The 7 elements you need for superior retention automation
It costs a lot to acquire a new customer, but most clients will make a single purchase and leave. A repeating purchase, on the other hand, costs far less than acquiring a new customer, estimated at between 4 and 7 times less actually.
Retention automation has a simple, well-known theory that deals with this issue. Retention automation aims to get better ROI by turning one-time buyers into repeat customers and keeping them, rather than focusing on acquiring additional new customers.
Retention automation can be done with the basic understanding that customers are different, then analyzing them as groups, connecting them to automated campaigns designed to move them in the right direction.
There are plenty of examples that demonstrate programs and multichannel campaigns addressing customer retention according to the customer’s current lifecycle situation and their importance to the business. Surprisingly, although the theory is so…
How Big Data and Predictive Analytics improve marketing
Predictive Analysis research and 'Big Data' is helping companies to improve their marketing, through accessing multiple sources of data and employing specialist staff to 'understand the data', providing actionable data which Marketers and Decision-makers can use to improve performance.
This IBM and the Aberdeen Group 'Big Data for Marketing' research set out to identify the ‘Best in Class’ practices for companies providing accurate information in an efficient way, to support key Decision-makers and their planning processes.
The Infographic below summarises the top strategies, results and capabilities:
It highlights that it has helped companies to become more efficient, improve their decision-making and overall performance, through actionable high quality data analysis. The detailed report draws out the technologies and business…