“Big data” may be the newest buzz word of today’s technological trends, but the sheer amount of data collected by a business is not the best indicator of its potential. The root value of data lies in not how much of it is gathered, but how it used by the collector. Maintaining current data could be the single most important factor to successful business, but data is essentially useless without interpretation. Interpreted data is the key component of actionable information, and quality reigns over quantity.
The terms “data” and “information” have become synonymous, but it is imperative to understand the contrast between them. “Data” describes any set of raw elements that have no identifiable relationship, and these elements are usually unfiltered. Pieces of data may be stored together, but other than that, there is often no real connection between them. “Information,” on the other hand, is basically the analyzed form of data, in which those raw elements have become usable findings. While data are similar to individual links in a chain, information is the set of those links forged together. The information generated from data is used to make logical assumptions.
What distinguishes “actionable information” apart? This kind of interpreted data can be utilized to make educated business decisions. In order to be actionable, information must be comprehensive, accurate, and timely so that credible and consistent decisions can be formulated. Thus, the best actionable information is projecting in nature; it looks toward the future by allowing the user to take corrective or preventative action in regards to existing or potential problems within a business. In email marketing, for example, the number of total emails sent out in a deployment is a piece of current data, but which emails bounced is actionable information; administrators can choose to delete the bounced email addresses from CRM records to prevent the company domain from being marked as a spam sender.
Most forms of basic data, however, cannot produce actionable information. Commonly, business will collect merely email addresses as their primary form of customer data, but what can be garnered from this alone? Phone numbers, home addresses, birthdays, employment, company associations, and purchasing history are just a few types of data that should be kept up-to-date for as many customers as is applicable. Traditional data collection methods have gaps that cannot accommodate all these pieces of data, and this is where data enhancement comes into play.
An increasingly popular form of data enhancement is data augmentation. This process involves improving the value of base data by adding more data derived from internal and external sources. While surveys could be sent out customers inquiring about the missing data that is desired, there are multiple online services that can provide whatever data is absent. These services function similarly to databases, holding various data on corporations, people, industries, and other business records. Many offer commercial business information through their online platforms, so other companies can jumpstart data cleansing and analysis.
The benefits of data augmentation are numerous. It can be applied to any form of data, but it has the highest potential in being used for customer data and product sales patterns. The additional data provided by augmentation will lead to information capable of giving in-depth insights into customer bases. Simply by interpreting augmented data, existing marketing campaigns can be improved, new ones can be created, and complex business questions can be answered.
A competitive business, for example, might desire to know what their typical customer looks like, or where they should build their next store. With only minimal data such as email addresses, no actionable information can be garnered, which means no answers to the aforementioned questions can be formulated. Augmenting that data, however, using GIS (geographic information system) or Census data obtained from outside sources will allow a business to make major marketing decisions after forming a better picture of their customer base. When customer data includes such aspects as gender, neighborhood demographics, and median income, identifying a typical customer becomes much easier.
This identification simplifies the task of planning new store locations. Demographic data in combination with customer addresses can be used to pinpoint customer hotspots, which can then be compared against current store locations and utilized to choose the best area for new construction. Acquiring and using data to build up information undoubtedly gives businesses a superior edge over their competitors, because it takes the guesswork out of important business decisions, increasing opportunities for success.
Once all actionable information has been determined from augmented data, the data itself can then be segmented. Data segmentation is the process whereby a customer base is divided into groups of individuals who are similar specifically in relation to marketing, such as age, gender, interests, location, and spending habits. Segmenting data will lead to more efficient and successful marketing, since it allows more effective targeting of groups, and marketing resources can be allocated accordingly.
Data segmentation, however, is impossible with merely email addresses and phone numbers, because neither type of basic data can provide actionable information about customers. Therefore, data augmentation is the necessary first step of any successful marketing campaign. After deciding what data will be collected and how it will be gathered, the actual collection and integration of data can begin, which is followed by developing methods of data analysis for segmentation.
These methods depend on what kind of segmentation will be best for a company’s marketing purposes. Traditional segmentation emphasizes the identification of demographic and attitude-based customer groups. Gender and industry affiliation, for example, fall under traditional segmentation. Value-based segmentation, on the other hand, focuses on customer groups in terms of purchasing habits and generated revenue. It aims to identify the monetary costs of establishing and maintaining customer relationships. Brand preference and date of last purchase are two kinds of value-based segmentation criteria.
Many organizations encounter difficulty in understanding the different characteristics of customers and prospects. Thus, marketing resources end up being wasted on communication with unlikely customers outside of the target market. Segmentation of augmented data can help to alleviate this problem, given that a business can implement appropriate measures to respond to the information provided by the data. By identifying the various levels of a customer base, a business can tailor and sophisticate their marketing resources and customer communications to best suit its target market or intended demographic.
In addition to augmentation and segmentation, it is crucial to keep data clean, or as current as possible. With outdated data, augmentation and segmentation are useless. There are several simple actions that one can take, easily accomplished with the CLS 4.0 system, to manage customer data.
Data can often be cleansed by removing obsolete pieces. Any contacts with phony or missing data should be deleted. If a customer has entered a fake phone number, such as 123-456-7890, it can be assumed that they do not want to be contacted, and their data is therefore of no use. Avoid any potential negative consequences of further contact.
Likewise, if a customer email bounces during a deployment and the contact cannot be updated due to a lack of data, it is best to remove the contact from mailing lists. This helps to ensure that a business domain is not marked as a spam sender or otherwise blacklisted. Sometimes the elimination of these kinds of contacts results in no remaining contacts for specific companies within records; it is wise to completely remove those companies from records, but this is at the discretion of the system users.
Besides deleting old customer data, there are other ways to keep data current. While these methods may not necessarily aid marketing campaigns, they will improve the proficiency and effectiveness of a company at completing tasks and projects. Any outdated reports and documents should be deleted. Searching through long lists of reports that are no longer needed is frustrating, and so is wading through useless documents when files for only one business account need to be found. Exercise precaution when reviewing invoices and contracts, being sure to remove anything too old for use.
The same idea goes for outdated marketing deployments, email templates, and users. Old and abandoned campaigns should simply be discarded. If just two or three latest email templates are needed, get rid of older ones to avoid time-consuming wading through files. If irrelevant tasks still exist that are too outdated to complete, delete them to minimize confusion. This also applies to prospects and opportunities that were not closed or do not exist any longer. The user administrator for the system should also take care to delete any users who do not work for the business anymore. Any employees who leave should have their user information removed so that they no longer have access to CRM data.
The tremendous benefits and best practices outlined above outweigh the detrimental problems businesses could face if they are deficient in current data to facilitate augmentation and segmentation. General lack of knowledge about customer and prospect bases, untargeted communications to customers and prospects producing low ROI, and incorrect messaging that leads to customer dissatisfaction as well as poor customer retention are all major issues that could cause business failure yet could easily be resolved with data enhancement.
Interpretation and segmentation of current, augmented data puts a company in the know as opposed to having to instinctively guess when it comes to making business decisions. Know much, while knowing more than others—market wisely, advertise better, and render your business’s chances of success as favorable as can be.