Article : Out With The Old, In With The New: Outbound Telemarketing Centers Deploying Intelligent New Technologies

The ideal telemarketing operation is not just a pipe dream — it's a reality for many call centers today that have deployed intelligent predictive analytic technologies to do what may at first seem impossible. By using intelligent technologies call centers may overcome many of the traditional telemarketing challenges and optimize their operations for maximum conversions and higher profits.

Every outbound telemarketing cross-sell, up-sell, and retention campaign triggers a set of critical questions for today's call centers:

How can we reach the customers who are likely to accept our offers?
How can we maximize our sales-per-hour?
How can we lower our costs-per-sale?

Despite their best efforts, many telemarketing operations are still struggling to find the perfect answers. However, within these questions lies a vision of an idealized telemarketing operation. Can you imagine it? It would no doubt include these timesaving and cost-generating features:

Robert Tate
Vice President of Marketing
Austin Logistics

You know every customers' propensity to be available and willing to accept a sales offer for every hour of your campaign.
Every customer's best-times-to-call are balanced and ranked for the highest impact (e.g., right-party contacts, sales-per-hour, lower-cost-per-sale) according to the best-time-times-to-call of all the customers in the campaign.
You balance this customer data according to your actual agent availability for every hour of the telemarketing campaign, and to ensure that you meet your goals and quotas despite staffing fluctuations.
The call lists are automatically scrubbed in real-time for Do Not Call compliance.
The entire optimized call list or lists is kept on schedule and critical adjustments are made in real-time by a centralized list management "brain" — across one call center or more and for an unlimited number of campaigns.
Unbiased champion/challenger testing runs automatically to ensure continual improvement according to your strategies and goals.

Can you imagine the results that could be attained in this optimized outbound telemarketing operation? They would surely include making fewer calls to reach right-parties, increasing sales-per-agent-hour, and lowering the cost of each sale. The overall impact would be significant profit generation to the company's bottom line.

Out With The Old
Contrast this optimized scenario with today's traditional list management operation where call centers' list managers painstakingly assemble and manage call lists all day long as goals change, staff levels fluctuate, and results are reported. Then agents start at the top of each list and call down over and over until they get a "hit." As a result, the revenue gains generated by sales are offset by the cost of managing the lists and excessive agent calling to each account.

However, the ideal telemarketing operation is not just a pipe dream — it's a reality for many call centers today that have deployed intelligent predictive analytic technologies to do what may seem impossible: Intelligently target the best times to call all contacts according to the needs of the entire call list and the actual agent resources that are available.

This idealized scenario may sound familiar to outbound marketing departments, which have a long history of precisely targeting customers for direct mail offers. But, this in-depth level of customer targeting has not been adopted by outbound call centers — even though the data is readily available. However, it is just as critical in the outbound calling world if call centers want to keep the cost-value equation in check.

In With The New
The two new technologies that are allowing telemarketing centers to overcome their old problems include best time to call predictive analytics and intelligent centralized list manager.

Best-time-to-call predictive analytics leverages customers' call histories and other data, such as third-party demographics, to determine the probability that each customer will be available to take a call and willing to make a purchase. Because it calculates the individual probabilities for each hour of the calling day, an entire day's, week's, or month's calling schedule can be optimized for the maximum conversions and cross-sells over the entire campaign. This eliminates the least responsive customers from the list according to companies' own cut-off criteria, allowing the call centers to focus their resources on the high-potential customers.

However, the best dialing strategy in the world won't deliver the highest results unless it is implemented consistently and without interruption. An intelligent list management solution helps call centers efficiently manage a single or multiple dialers in one or more call centers to reduce resource costs and make dialer operations and campaign management more effective. In this way, the operation can easily execute sophisticated list management capabilities, such as shutting down a low-performing list and deploying a new list without interruption.

	Out With the Old	In With the New
Calling Strategy	Non-scientific top-to-bottom strategy	Sequence customers into the most productive calling schedule for every hour of the day
Agent Resources	Add more resource costs to improve results and cover "prime" calling hours	Reach more right-party contacts without increasing agents by distributing workload based on actual available staff
Business Objectives	Dictates off-strategy calling agendas, forcing call centers into less than optimal call strategies	Gives companies' specific calling objectives priority, such as calling retention risks first
Continual Improvement	Runs biased tests that cannot accurately predict the best-performing call strategy	Employs unbiased built-in champion/challenger testing functionality to support continual improvement
Late List Arrival	Disrupts workflow and productivity, and forces agents to work old lists with outdated account information	Applies contingency strategies for late list arrivals and executes real-time list synching to keep all lists current
Multi-Site Management	Dedicated dialers restrict operational workflow optimization	Shares workloads across multiple centers to increase productivity and continuity

Telemarketing Intelligence In Action
A perfect example of what telemarketing operations stand to gain from these two intelligent solutions is a financial services company with a diverse range of financial products, including home equity loans, checking and savings accounts, car and personal loans, and money management activities. Like many businesses today, this company realizes that one of the most powerful ways to increase long-term customer loyalty is to increase the number of products its customers own. To achieve this goal, the company's three telemarketing call centers conduct ongoing up-sell and cross-sell campaigns for a wide variety of products, such as credit card offers and overdraft protection.

Customer Targeting
Out with Low Sales-Per-Agent-Hour. Despite several strategies designed to improve sales, the sales agents were not consistently reaching the parties who actually had the propensity to buy, which resulted in fewer sales-per-agent-hour than the company had targeted. One of the problems was the call centers' very common calling strategy of sorting the lists on a wide variety of parameters, then starting at the top of the call lists and dialing to the bottom, and repeating this process throughout the day.

In with Best-Time-to-Call Targeting. Now the agents reach the most eligible buyers first, rather than just those who are easiest to reach. As a result, this telemarketing operation gained a 20% lift in sales-per-agent-hour, without increasing the size of its agent staffs.

Agent Scheduling
Out with Unrealistic Workforce Schedules. A significant problem was the call centers' inability to accurately schedule agents to meet actual workload requirements — despite a workforce prioritization application purchased specifically to solve the problem. This program calculated an idealized agent schedule based on the company's sales goals, often recommending either an agent resource beyond the call centers' actual staff size or creating a schedule that could not be met. As a result, the call centers typically had problems with split shifts and unmanageable schedules.

In with Optimized Agent Scheduling. By aligning the calling needs with actual staffing capabilities, the company is no longer forced to fit its agent schedules into unrealistic workforce projections. Instead, the call centers exactly match their workload to their exact agent resource.

Continual Improvement
Out with Biased Champion/Challenger Testing. Once the call centers started improving their results, they wanted to test their campaigns to maintain a process of continual improvement. Previous campaign testing methods had been ineffective due to biased data. There were too many variables for the call centers to control to conduct unbiased tests, such as a wide range of agent skill levels, different days of the week, different times of day, and different weather conditions.

In with Unbiased Champion/Challenger Testing. This telemarketing operation conducted a variety of unbiased tests, including a three-way experiment testing its business-as-usual (BAU) operations against a strategy to increase contacts and a strategy to increase sales. When the call centers worked to increase contacts, sales bumped up 10 percent over BAU. But when they configured their strategies to increase sales, they increased sales by 20 percent. The centralized list management application facilitated clean, unbiased testing controls by allowing multiple lists to be fed into a single campaign with a single agent pool.

Do Not Call Compliance
Out with Automated Do Not Call Processing. The telemarketing centers had been paying high costs to scrub their lists according to ever-changing Do Not Call regulations — and high fees for any mistakes they made.

In with Automated Do Not Call Scrubbing. This operation gained a substantial additional bonus benefit: real-time integration with today's Do Not Call lists. This saved the telemarketing centers' the high cost of manually scrubbing their lists — and protected them from Do Not Call fines.

Bottom Line
This telemarketing call center and others are enjoying a new world using intelligent technologies that overcome many of the traditional telemarketing challenges and optimize their operations for maximum conversions and cross-sells, increased sales per-agent-hour, decreased costs per lead, and higher profits. Imagine that.

About Robert Tate:
Robert Tate is the Vice President of Marketing at Austin Logistics, a provider of analytic software and solutions. Tate has more than 10 years of experience in call center management and operations. He has held executive-level positions at call center hardware and software technology firms. Tate previously served as vice president of marketing for Latitude Communications and Vantive, where he was part of the management team that drove the successful acquisition by Peoplesoft. Tate holds an undergraduate degree from the University of Southern California and a graduate degree from Duke.

About Austin Logistics:
Austin Logistics' products and services are trusted by many financial services companies to dramatically increase the value of customer interactions, simplify operations and help achieve business-specific objectives in the areas of collections, risk management and customer service.