Case Studies

Case Interview - Market Intelligence for Marketing & Sales

Cisco's Customer Intelligence & Econometric Models

Interviewed for this case is Joost Drieman, Market Intelligence Director Europe at Cisco Systems, on how Cisco supports its strategy and business development management activities through sophisticated research, analytics and econometric models, as well as what kinds of measures are being used in the company to demonstrate the value of the intelligence operation.

Background on Cisco Systems

Cisco enables people to make powerful connections-whether in business, education, philanthropy, or creativity. Cisco hardware, software, and service offerings are used to create the Internet solutions that make networks possible providing easy access to information anywhere, at any time. Cisco was founded in 1984 by a small group of computer scientists from Stanford University. Since the company’s inception, Cisco engineers have been leaders in the development of Internet Protocol (IP)-based networking technologies. Today, with more than 65,225 employees worldwide, this tradition of innovation continues with industry-leading products and solutions in the company’s core development areas of routing and switching, as well as in advanced technologies.

The 5 Pillars of Intelligence – Cisco’s Intelligence Structure

“We are the eyes and ears to the market at Cisco”, says Joost Drieman, from his office in Brussels, about the European Market Intelligence team that he is heading. “We serve as navigators for our strategy, marketing and business development people who work to win new business in the competitive marketplace.”

The European Market intelligence organisation at Cisco have been built in to the “five pillars” that it’s sophisticated intelligence operation rests on. The graph below illustrates how the intelligence system serves the company’s different internal customer groups.

1. Macro Intelligence (“Euro/ Country Dynamics”): Monitoring and analysis of political and macroeconomic issues, social trends, legislative issues and environmental topics and understand the relevancy of these findings for Cisco’s business in Europe.

2. Verticals and segments: Monitoring of segments such as finance, retail, manufacturing and the public sector in order to understand the industry growth drivers and the subsequent needs for present and future solutions that Cisco can provide.

3. Customer Intelligence: Monitoring the (potential) customers in the market landscape that consists of the total addressable and adjacent markets for Cisco’s products and services by region, by vertical, by sizeband and by technology focus. Understanding the potential to further develop existing accounts by using a set of econometric models as well as to identify new opportunities.

4. Competitive Intelligence: Building on the several models like Porter’s 5 forces (industry rivalry, the power of customers, the power of suppliers, new entrants, risk of substitutes)

Competitors: Looking at the competitive landscape and into the competitors’ capabilities like position, behaviour, gtm model, strategy and sales offering. This is important for the business development people to understand in order to be able to focus on those customers that are not locked in with a competitor’s solution. Equally important is to identify Cisco’s unique selling points vis-à-vis the competition.

5. Channel Intelligence: In Europe Cisco’s products are sold through Partners, which makes Channel Intelligence a vital area in the intelligence framework. Cisco is monitoring their 1st and 2nd tier resellers, system resellers, direct sales partners, integrators, distributors, as well as emerging channels.

Joost Drieman mentions that they are continuously looking to what type of companies the emerging channels for Cisco’s products could be.

Customer Intelligence guided by econometric models

Understanding existing customers

The Customer Intelligence unit at Cisco is responsible for maintaining a map of existing and potential customer companies in each region where Cisco operates. In this context, existing customers are evaluated from a risk perspective to their level of satisfaction and loyalty towards Cisco.

For each level of satisfaction and each individual customer, opportunities exist for either up-selling, cross-selling, or migration. “We have developed a sophisticated set of statistical models in order to understand both the risk and the business opportunities within each category of customers that we have”, Drieman says.

Cisco has developed a set of “buyer rules”, principles that seem to guide the customer’s behaviour in different scenarios. The result is an econometric model based on the long experience Cisco has of the IT solutions market and of their customers. Variables in the model include things such as number of employees, number of PCs installed, number of telephones, distance between offices, IT profile, purchasing patterns, number of remote locations, and the company’s growth pattern.

“Based on our model about the anticipated developments in our customer companies, we are well equipped to understand the life-cycle of our own solutions, and can consequently be proactive in proposing new ones when our analysis so suggests”, Drieman explains. “Indeed our marketing and business development teams have good experiences about the model’s accuracy: Successful sales is largely about good timing, and through using our model we have had a very good hit rate at identifying the situations where our customers are looking to purchase completely new systems or to migrate from an older generation solution to a new one”, Drieman continues.

“How we do this?” Drieman smiles: “The model itself is of course our confidential information, but it combines regression analysis, decision trees, multivariable analysis as well as neural network analysis into a whole that covers more than 200 analytical aspects. The main framework is based on an OLAP system that is populated with data that can be purchased from public company information databases and internal data.

Buyer propensity analysis

“Prospect analysis is also something that is very much at the core of our intelligence services”, Drieman says. “Based on what our model tells us, we will determine which companies in our target groups would probably be potential new customers and where our sales force should spend less time in being successful. Again it is very much about timing and efficiency: Our intelligence operation directly supports sales in pointing out where the resources are probably best spent at any given time”, Drieman highlights the system’s benefits and linkage to new business generation.

Measuring the ROI of the intelligence activities - Key Success Factors

Joost Drieman lists out the following Key Success Factors that Cisco has identified for its Customer Intelligence operation.

Quality of input data – In its models Cisco uses a large number of sources for data validation in order to avoid the “garbage in, garbage out” effect.
Sophistication of the model – The smarter the model is, the better the result. The number of data points for each analytical model is key.
Usage (by marketing and account managers) – All marketers and account managers need to understand the benefits of using the analysis in demonstrating the ROI of the intelligence/sales activities. Constant communication between management and sales people is needed.

Drieman views the ROI of intelligence activities as a specific area of expertise, and Cisco has developed models to improve their understanding of the subject. “One way we are doing this”, Drieman explains, “is that we compare the amount of new sales generated to the companies included in our Buyer Propensity model to the sales generated to a control group that consists of companies that our sales people are targeting outside of the model. This is a simple approach to calculating ROI for our intelligence activities, and we are using it to understand – and to demonstrate internally - how much intelligence is worth for the company”, Drieman continues.

According to Drieman, additional success factors in supporting customer processes with high quality intelligence input have been identified at Cisco as follows.

Approach to set-backs – “If we are not able to sell to a customer, we are not looking at this as a loss, a failure. Instead we see it as a temporary set-back. If we have identified the company as a good potential customer, we ensure that we keep trying to understand their needs better through good customer intelligence and on-going dialogue.”

Listening to the customers – “Customers are of course very different and should be approached accordingly. Even though our econometric models have proven their worth, we of course need to go beyond the hard metrics and understand the soft issues in how companies purchase IT solutions. We are trying to understand the following parameters.”

Buying criteria – What, when and how the customer decides to purchase
Support needs – How important training and interaction are for the customer
Price and value – How the customer values the products and services that Cisco provides
Product feature perception – Whether the solution should “just get the job done” or whether higher level of sophistication will be required
Ease of use vs. complexity – What is the customer’s capability and willingness to handle complexity in IT solutions
Decision maker – Who is the ultimate customer (CFO, IT Director or someone else?)

Understanding new business models – “This is important both because we need to understand our customers’ business, and because we very much depend on the channel business today. We are very well aware of the fact that our customers uses the network for business. ”

Learning the lessons when the market intelligence message was not heard – “It is vital to understand why intelligence may not always be utilized properly, and what happens if is not. We try to identify these situations and learn from them.”

Finally on an overall level, Mr Drieman summarizes that Cisco’s capability to support strategy, marketing, business development, as well as sales and account management through high quality intelligence activities is a function of three main variables, nothing more and nothing less:

Collaborative development of content
Synthesis of analysis models
Having a future oriented perspective

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