Customer analytics techniques boost sales and service strategies

Tanusha - Fotolia

How analytics in marketing can transform organizations

Marketing is second only to sales in terms of analytics application -- and it's where the odds of business success can most effectively be changed for the better.

Possibly the single most effective use of analytics in the enterprise is to strengthen the relationship between company and customer. The application of analytics to sales is obvious: to optimize the customer journey. But analytics in marketing plays a central role, as well, by greatly improving the odds of finding customers in the first place, which enables sales to approach them with the best possible message.

Analytics are applicable throughout the product marketing cycle in very effective ways. As with any tool, however, it's vital to use the right one for the right job.

Measuring intent. Finding customers is the beginning of the marketing process. The new environment for that search is social media, where a digital approach to marketing is now the standard. Social media monitoring puts the sentiment, behaviors and (sometimes) demographics in marketing's hands. These are descriptive analytics; data that helps define potential customers.

Scoring leads. With these descriptive analytics, it is now possible to move on to predictive analytics in order to score potential customers according to their likely behaviors. Will they buy or not, and under what conditions? These models inform the remainder of the marketing cycle.

Segmenting the audience. Armed with these analytics, the next step is to focus the marketing effort by segmenting the potential buyers into groups: those who will buy with or without prompting (put no money there); those who won't buy, with or without prompting (put no money there); those who might buy if prompted (put money there); and those who won't buy unless prompted (put money there). This segmentation clarifies the playing field and ensures more efficient spending.

Crafting the message. Once the target audience segment has been defined, the best way of reaching out must be determined. Analytics can greatly enhance this process; the resolution of customer-specific behavioral analytics, made possible by analyzing click patterns on the company website, enables a very focused pattern of messaging and presentation. It is possible to take small groups of customers, and even individual customers, and design a campaign that will cater to their individual needs and behaviors. This is done with a combination of descriptive and predictive processes.

Finally, there are prescriptive analytics, which define the best course of action based on the available data and predictions. This comes into play in campaign planning and execution.

The benefits of analytics in marketing campaigns

Once the previous processes have been analytics-enhanced, a course of action must be selected. Prescriptive analytics is the solution; given the descriptive audience segmentation data and the predictive behavioral data, prescriptive analytics can deliver guidance for crafting the best campaign. There are several points where these analytics are well-applied.

Content improvement. Previously, crafting a buyer-specific, campaign-specific message was a precursor to the campaign itself. Prescriptive analytics help marketers to zero in on the most effective messaging for particular buyers. The success of various messaging approaches in the past can be applied, and changes in both buyer habits and shifts in online sentiment can signal the need for fine-tuning.

Prescriptive analytics help marketers to zero in on the most effective messaging for particular buyers.

Campaign monitoring. Improving campaign content dynamically helps fine-tune prescriptive recommendations. It's one of many areas where monitoring can improve the progress of a campaign, from basics such as "Are we reaching the customers we're targeting?" to "What is the closing rate, and is it steady?"

Brand development. Part of campaign monitoring includes tracking brand sentiment via social media monitoring during the course of a campaign. This is a descriptive, not prescriptive, task, but it measures the effectiveness of the prescriptive course, and it signals any necessity for fine-tuning messages or channel deployments.

Competition monitoring. While a campaign is underway, it is important to continue monitoring the competition, again, via social media monitoring. This adds an effective indicator of the campaign's effectiveness for subsequent scoring and evaluation of results.

Campaign resources. Prescriptive analytics can analyze potential expenditures for various campaign approaches to determine which offers the best ROI. In addition, analytics can be used to monitor expenditures as a campaign progresses.

Common mistakes in marketing analytics

Once an organization has embedded analytics in marketing processes, it's easy to let the implementation of an analytics application drift and lose effectiveness. Here are some common errors.

Complacency with channels. Establishing social media monitoring of various channels to customers is a major accomplishment, providing perpetual information about customer behaviors and sentiment regarding the brand. But new channels are opening up all the time, and old ones can sometimes drift as the buying audience ages. It's important to constantly seek out new channels and to continuously retest existing ones.

Complacency with process. When it comes to business intelligence, it's not uncommon for a "weekly reports" mentality to creep in; once analytics are in place and proven, there's a tendency to simply rely on them and forget they're there. But marketing analytics are sensitive to a great many changing conditions; they require constant tuning. This should be a commitment from day one.

Complacency in evaluation. Since analytics are sensitive to changes in market conditions, a constant alertness needs to be in place so that tuning can occur when needed. It's easy to simply assume that's the job of the chief marketing officer -- but it isn't. Since the conditions affecting analytics occur at every level, there needs to be diligence in analytics process evaluation at every level -- from the sales rep to the sales lead to the sales manager on up.

Analytics and the customer

This is the second article in a three-part series focusing on the role of analytics in sales, marketing and customer service.

Finally, applying analytics to marketing performance itself is paramount: By scoring in-house processes throughout the cycle, it is possible to accurately measure ROI and have solid predictions of the success of anticipated changes in processes. Here, again, diligence is the key.

Next Steps

Trident Marketing uses analytics to reduce customer churn

Professionals share their perspectives on prescriptive analytics management

The future? It's prescriptive

Dig Deeper on Sales enablement tools