Hours of time and effort are put into creating content, only to discover that the subsequent email campaign has little to no effect on sales and conversion rates: it's one of a marketer's most disappointing scenarios. Bounces and blocks are satisfactorily low in number, and open rates are high, meaning subscribers saw and read the emails. Click rates, however, are dismal, prompting a reasonable marketer to question, "What is going on here?"

The situation outlined above is not necessarily indicative of poor content quality, but low customer interest, as evidenced by the subpar click rates. A common problem facing marketers is that they have neither a complete understanding of their customer base nor a clear picture of their average customer. This issue can be difficult to resolve because it is not always recognized to begin with.

Traditional email marketing tactics focus upon collecting basic information, such as name and email, in order to build up subscriber lists. Deployments as well as newsletters are then sent out en masse, in an attempt to market to the entire audience. Campaigns set up in this fashion are likely to produce less than desirable results, because customer bases are often too diverse for them positively respond to one-size-fits-all messaging. Sometimes, it is easy to forget that email recipients are individual people who are simply a part of a larger group, not the definition of it. Therefore, it is key that all demographics within a customer base are targeted.

Targeted email marketing is a surefire way to improve click rates and thus aid in increasing sales. Not all members of an audience may respond to a specific kind of product or publication, due to their personal interests and preferences. Rather than relying on generalized messaging, the most successful marketing campaigns involve determining which customers respond best to what kinds of content. Specified emails are then sent out to different customer groups based on the findings. Targeted messaging is a more efficient and cost-effective form of marketing, since less resources are wasted by a business as appropriate audience members receive the content they want, which simultaneously betters conversion rates and customer loyalty.

How can a business go about identifying customer preferences and creating these specified messages? Driving this action lies in the proper collection and utilization of data to garner information. The simplistic data of name and email address is not enough to market effectively, because no actionable information can be derived from them. Businesses need to go beyond those two criteria and collect phone numbers, addresses, birthdays, gender, relationship status, employment, company associations, and even purchasing history. All this data should be kept current for as many customers as possible, but traditional data collection methods are somewhat lacking when it comes to filling in all the gaps.

To meet this shortcoming, data augmentation is rising in popularity. It is a form of data enhancement whereby existing data is added to by internal and/or external sources. While it is true that surveys can be sent out to subscribers requesting the missing data, many businesses are now turning to online services that function similarly to databases. These services commercially provide data on corporations, industries, people, and other business records through their online platforms.

Data augmentation is best applied to customer data and product sales patterns,since it leads to highly useful actionable information that can be used in making business decisions. Interpreting augmented data is an excellent method for identifying the typical customer; when name, age, and gender are supplemented by Census and GIS data to determine geographic location, employment, and income, among other criteria, painting a portrait of the average customer is not complicated. The knowledge gained from this process can then be used to appropriately segment the data.

Data segmentation involves the splitting up of a customer base into different groups for marketing purposes according to various criteria. Traditional segmentation focuses on dividing customers based upon similarities in physical attributes, attitudes, or demographics. Value-based segmentation is geared more towards how much revenue customers generate, as well as the cost of maintaining customer relationships; this type divides customers based upon criteria such as date of last purchase and brand preferences. Both kinds of segmentation would work well for businesses in general, but e-commerce businesses would benefit especially from value-based segmentation.

After data segmentation is achieved, it can be used in terms of email marketing by appropriately placing customers onto specified marketing lists. Products, deployments, and newsletters can then be tailored to fit the average customer, and this content can then be further modified to be better suited for other major demographics. Once a deployment or newsletter has been created, it can be sent to selected marketing lists rather than every subscriber. New content can be sent out in an effort to attract potential customers based upon the demographic information already known. Essentially, separate content and different products can be marketed to smaller groups within customer bases in order to provide them with marketing that they will actually respond to.

Sending out specified messaging can be facilitated by the Cool Life CRM system with proper use of the query feature in the main CRM grid view. The user has the ability to access the pages of customer records belonging to a particular table or list. These displayed records can be filtered with numerous chosen criteria, and they can be manipulated in several ways.

Records must first be selected, and there is a menu option for quickly selecting and deselecting entire pages of records. The total number of currently selected records is also displayed. After desired records have been chosen, they can be manipulated using the actions menu, which features various options such as export, print, add to list, mass update, merge, and delete.

The grid filtering interface allows the user to search and filter the selected records with the criteria of their choosing. Any set filters will be saved, and they will pre-populate the interface whenever it is revisited, unless they are cleared. For the purpose of messaging facilitation, switching to the advanced filters mode offers a much greater level of control and flexibility in creating filter criteria. Fields can be added to the filter configuration by dragging them from the field list into the filter group.

The filter group is the mechanism for organizing fields into logical bunches. If needed, additional sub-filter groups can be added to the filter configuration, which can accept more fields or filter groups. Thus, when filter groups are used in conjunction with the group operator setting, highly complex filter criteria can be produced. For a text-only representation of the filter configuration, the file structure bar must be turned on, and it can then be used to check the logical order of the criteria.

Using the filtering mechanism, contact lists already input into the CRM section can be searched and analyzed, which is what facilitates specific messaging.  Records can be searched all at once, and then the selected results can be placed onto marketing lists for later communication purposes, such as deployments and newsletters. Among the criteria that can be searched are city, phone number, company name, email, relationship status, title, and status as a primary employee, but the various filters available depend on what criteria have been established as a part of every CRM record.

Assume that a company's average customer is a married man working in the financial industry. After all CRM records of male customers are selected using the simple filtering, the advanced filtering can be turned on. The filter group of "relationship status" can then be added to the filter configuration, and it should be set equal to "married." The filter group of "primary industry" should also be added and set equal to "financial." Because the results need to fit both criteria, the operator should be set to "AND." These settings will filter through all the selected customers to show only married men who work in the financial industry. Their records can then be added into a new list for whatever marketing purpose is desired.

On the other hand, a company might regularly send out product updates to its individual customers, while it wants to expand its content to include newsletters sent to the primary contacts or CEOs of their business clients. In this case, the "is company primary contact" field should be set equal to "yes," while the "title" field should be set equal to "CEO." The operator must be switched to "OR," because instead of looking for only primary contacts who are CEOs, the criteria are meant to search for either primary contacts or CEOs. Thus, there will be filtered results of primary contacts who are not CEOs, CEOs who are not primary contacts, and people who are both primary contacts and CEOs. The Cool Life CRM system makes tailored marketing in situations such as this easily accomplished.

Any marketing effort made without data augmentation and segmentation is more or less a shot in the dark, because lack of knowledge about a customer base and its diversity can be detrimental to long-term business success. Marketing to subscribers who are unlikely to respond or sending out generalized content missing the target market's interests both contribute to poor customer retention and greater customer dissatisfaction, leading to eventual business failure. These problems can be resolved, however, with a properly informed division of the customer base into appropriate marketing groups. Once content has been shaped to target specific audiences, Cool Life CRM's filtering feature makes sending out that marketing material quicker and more accurate. While the processes of augmentation and segmentation do require the investment of time money, it is, simply put, well worth the increase in ROI, brand awareness, and customer loyalty.