Big data analysis brings precision marketing into the enterprise

New marketing development software helps companies extract value from ordinary sales methods - giving them a firm grasp of existing customers.

In 2013, Russ Hearl began trying to expand his company, Double Dutch in San Francisco, to establish a market for social networking software and activities. In a team of only three salespeople, developing this market from scratch required a lot of hard and intense work. They were on the phone every day, but they still didn't know who the target customers were.

Hearl, Double Dutch's vice president of global sales development, said: "Our sales team was actually expanding the business in isolation. There was no systematic growth momentum at all."

Because The social conferencing software was still a young market, lacking web exposure and not yet even a business through search engine optimization - the keywords researchers used to drive traffic to a company's website. So his siled members still had to use some old-school methods to grow their business: making phone calls and pitching business cases for virtual conferencing software one by one.

However, telemarketing is a difficult job. Calling a stranger without knowing their background is very inefficient. Double Dutch needed better information to be able to mine the many sales, understand who would never buy from us, and find some of the meeting technology decision makers. About a month after implementing Salesforce.com, Hearl launched Inside Sales marketing development software, which can help his team find companies that are truly interested in his software and people who have the power to make purchasing decisions.

Hearl said: "I want to minimize the waste of time, and calling people who have absolutely no interest in the business is a waste of time." Inside Sales allows Double Dutch to discover event planning at these companies number of users and then focus on those aspects. Hearl noted that so far this year, the sales team has identified 350 real opportunities out of 3,000 leads generated while maintaining the same budget.

Obviously, the involvement of data companies with information about potential customers is clearly needed here. According to a survey conducted by Decision Tree Labs in 2013, 59% of B2B marketers lacked confidence in their marketing scoring models due to incomplete information; another 44% said they did not know which attributes can reflect purchasing behavior. .

Brian Kardon, chief marketing officer of Lattice Engines, another marketing development software company, said: "The real challenge is the trouble with volume. Sales can call any number of potential customers. But the problem is: 'Who should I call first and who is most likely to buy the product?'"

An emerging market

Inside Sales is a new type of software that specializes in collecting company data (internal and external), and then optimize the analysis of potential and existing customers. Some call it marketing automation, some call it multi-dimensional marketing outreach, and some call it sales acceleration software.

Whatever it’s called, the technology uses data to help companies better identify potential sales based on complex criteria, drill down into relationships with existing customers, and then discover possible business before they do so question. These technologies can combine data from external databases (such as Google Cloud) and corporate records with the company's internal CRM, sales and other customer data.

Todd Berkowitz, research director at Gartner, said: "When the marketing software services companies Marketo and Eloqua came on the scene, you could only hand some marketing methods to the sales people and let them demonstrate what they were and what they were doing. What has been done on the company's website. This approach will continue for a while, and then we will see some changes in the purchasing process, that is, the power of suppliers is weakening, while the power of buyers is increasing. Problem."

Now, a number of startups have announced their entry into this part of the market, including Inside Sales, Lattice Engines, and Salesfusion. These vendors say they can help companies optimize real-world marketing based on predictive conditions—discovering which customers are ready to buy and which existing customers they can sell more products and services to. For example, Juniper Networks, also a Lattice Engines customer, found that some new customers had recently moved into new offices and were ready to purchase switches and routers. Other alerts might include a new patent or receiving a large government order. "What you want to look for is a sign of activity that signals a buying cycle," said Lattice Engines' Kardon.

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Build better customer relationships

SunTrust Bank in Atlanta, USA, is a local bank that generates business by digging deep into customer relationships. Andrew Yearwood, Bank Vice President and Business Consultant pointed out that before the bank started using Lattice Engines, it used various internal systems to collect customer information in order to prepare a sales call. This process was very time-consuming and inefficient, and it may not obtain the correct customer information in a timely manner. p>

Yearwood described: "You have to log into multiple systems, and each system has a separate login account. Some are mainframes, some are based on the Web, and some have deep folder levels - it is simply not as simple as a click to generate a report. Therefore, most salespeople will admit on the surface that they have not done a good job, but in their hearts they think that the company should provide me with some conditions to help me do a better job. ”

Meet Lattice Engines

Yearwood pointed out that by using Lattice Engines, sales staff now only need to use one system to access existing customer information and discover what they may need. A number of products and services.

If you are a company and you have an audit accountant, we have many other types of products that can help you manage your cash flow. We can help you complete your business with reports and control the security of payments, disbursements and other services. We can use this data to understand how customers are using these tools to run their own businesses, or if there are unpurchased solutions. "

Gartner's Berkowitz said: "Customer lifecycle management will bring great opportunities for cross-industry sales and up-selling. Not only will you get external data, but you will also enrich the data in your own database. This is a very powerful forecasting tool. ”

Yearwood pointed out that the company plans to apply this software to more aspects next year, such as marketing development, but there is still a lot of work to be done.

Weighing the pros and cons

Even though these tools have many advantages in improving productivity and helping sales teams, the software is still in its nascent stage, and it has some limitations. For example, Yearwood hopes that Sun Trust can provide a more flexible view of the data.

While Lattice Engines "does a good job of showing snapshots, we would have preferred it to be able to show trend data and time series data," he said. And it can't do that yet. "Seeing changes in data over time and then comparing data from year to year can provide a more substantive interaction between bankers and customers when discussing cash flow or credit card usage trends." In these conversations, you become an advisor and act as a strategic guide. "

Gartner's Berkowitz also reminded that companies should consider some internal assumptions, and these technical models will use these assumptions to determine the judgment criteria.

He said: "The biggest factor of this software is The problem is that it's a black box. Some companies are afraid to trust black box models provided by others because these algorithms are confidential. "Berkowitz noted that he would also try to differentiate between the different vendors in this space.

"At this point, they are all the same," Berkowitz said. However, there are some vendors who may claim: ‘We have open sourced the algorithms and then provide services around those algorithms. ’ Then this is a difference.

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