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 capabilities of those being used by ‘Best in Class’.
Analyst says that ‘customer analytics has become the driving force behind
big data developments,’ so it’s of little surprise that many of the
“best-in-class” enterprises in the report came from the fields of retail and
telecommunications. Rowe also said specific use cases are popping up as having
big, quick returns, like fraud detection in financial
services or the analysis of sensor data in
utilities.
They surveyed 125 organisations across the globe, with an on-line survey
to identify:
·
Data collection sources
·
Efficiency to manipulate and analyse data
·
Accuracy and quality of data.
·
Tools and resources to support this.
Some of the findings concluded:
·
93% relied on their data quality
·
35% realised a year on year increase in ‘accessible data’
·
successful companies up-skilled staff in analytics with training and
external Analysts to support them
·
those ‘Best in class’ were 5x more likely to have a ‘Data Scientist’
·
companies experienced improved data agility through analytical
exploration and drill-down tools.
Reference:
In the business world, there is a connection between the business and the customers, and the relationship between business and the customers is built up in market. Data seems always massive and could be gotten from so many different kinds of sources, the different thing is that the organizations should have a shrewd sight in every channel to get data and should have a piercing sight in data analyzing results. In fact, all the resources of collecting data could be separate into four different parts, operational channel, financial channel, constituency channel, and customer channel. First one is operational channel, and operational business data are from customer relationship management systems which are used to follow the customer interactions with the company, and machine sensors which are used to follow the important performance metrics across worldwide implementations. Second one is financial channel, and financial business data are from the company’s financial reporting systems. Third one is constituency channel which includes employees and partners, and constituency data contains many objective data such as attitudinal data and specific constituents. In this section, human resources department has an important role to collect lots of data with a big range from performance histories and completed training courses to survey results and salaries, in addition, partner programs can follow the partner information which includes attitudes, financial investments, and sales growth. The last one is customer channel which includes structured data and unstructured data, and in some big organizations, they build up their enterprise feedback management programs to collect and analyze data from surveys, social media, and online communities. There is also an interesting and helpful link: http://businessoverbroadway.com/big-data-advances-in-customer-experience-management
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