In my last post, I discussed how traditional behavioral data analysis differs from contextual data, which I defined as information that is delivered to the right person at the right time within an actionable context. Today I’ll discuss the three broad types of data that matter most to sales agents.
In enterprise companies, inside sales agents often have vast numbers of leads, opportunities and contacts at their disposal. Occasionally, sales managers will order very simple directives, such as to call down a specific list that has been prepared for their teams. These are often prospecting campaigns. More often than not, however, sales agents are simply expected to sell, and prioritization is often a daunting task.
One of the goals of the marketing automation era has been to deliver prioritization data within the context of a sales agent’s CRM. For example, a sales agent working within a CRM can access an automated list of priority contacts. Connecting with any sales agent is as easy as clicking on one of the names, and clicking to send a message or call.
Lead scoring, now a well-established convention, is one of the best features to come out of the marketing automation era. The end goal is to show sales reps which leads and contacts should take sales priority, and attempt to predict sales readiness. To do so, marketing automation systems assign a predetermined numerical score to specific behaviors or statuses within a database.
An example of status-based scoring is by job title. Specific keywords within job titles can be assigned a numerical value. For example, a CIO might receive +10 points simply for his status, whereas an “administrative assistant” would receive zero, since the likelihood of the latter being a decision-maker is relatively small.
Alternately, scores increase for behaviors such as filling out a contact form, visiting pricing pages on a website, or registering for a demo. The result of all this data is improving sales agents’ success by focusing them on priority leads within context.
Lead scores are great for prospecting, but sales teams have to be agile. The best companies handle urgency through alerts that are delivered within the context of CRM, email messages or their phone.
Lets start with the telephone. These days, all inbound sales calls should be considered urgent. This is true across a wide range of industries, including travel (calls are proven to drive more revenue that online transactions), SaaS (where a call indicates an buyer at an advanced stage of readiness) and nonprofits (where telephone-based fundraising is still so common).
Sales calls should always be routed to the right agent or group. As one example, at RingDNA, we created campaign-specific routing. It works like this – a marketing manager instantly creates a campaign-specific or product-specific phone number, which can be used in any online or offline channel, such as Google AdWords, a specific page of a website, a social media campaign or a radio ad. All calls coming in from that phone number can then be routed to a specific group of inside sales agents. Outside of normal business hours, those calls can be routed to an office in another time zone, or be configured to play special voicemail messages. Along with these calls, RingDNA also delivers a bevy of contextual data, which we’ll explain more in the “opportunity data” section.
Other examples of urgency data are telephony-based rules for online behaviors, such as demo requests and eBook downloads. For example, when a prospect fills out a form requesting a demo from a sales agent, business logic can be applied to immediately call the prospect and attempt to connect them with a sales team, who is alerted by both email and within the call queue on their phone that the system is trying to connect with a prospect. Immediate response activities such as this dramatically increase the likelihood that the contact will result in a sale.
Finally, there are a number of solutions that determine urgency within the context of the CRM. Previously, we discussed how lead scoring helps with outbound prospecting. Marketo uses these scores, along with other factors, to predict which leads are “hot.” The result of their calculation is displayed in their sales insight product, which is viewed within Salesforce.com and other CRMs as a tab item, with heat measured by fireballs and flames.
The newest form of contextual data is what I call opportunity data, because it is by far the most important factor in creating enhanced close rates. Opportunity data shows sales agents want prospects want (desire), and what to sell them (action).
Earlier, we discussed the importance of routing campaign-specific calls to the right sales closer or team. Along with the call, RingDNA also routes important data that is delivered within the context of their softphone or mobile device. For example, if the prospect conducted an online search before calling, the call is delivered with the prospect’s search keywords, which clearly shows desire and intent. Additionally, the call is delivered with campaign-specific sales talking points, so that the sales agent knows what to sell them.
In addition, RingDNA delivers social data with the call, harvesting prospect data from LinkedIn, Twitter, Facebook and even Yahoo news. What’s really amazing is how well and how fast the data can be delivered during, or even before and after the call. This adds immediate value, and makes sales calls much smarter. The value in seeing this in the context of an iPhone, iPad or web browser can’t be underestimated.
Finally, collaborative team data via Chatter is delivered at the moment of the phone call. This is really important in environments where multiple sales agents may be working on the same deal. For example, if the Chatter feed shows that Ashley posted something about the account the other day, it may help to mention that to the rep, or at the very least, not to contradict what was already said or done.
The result of all this is a platform for providing sales agents with rich, contextual data when they need it most. But the data that RingDNA and these other amazing solutions currently offer is just the start. Expect a lot more innovation in the area of contextual data delivery down the road, both to sales teams and others in the organization.
Howard Brown is a three-time entrepreneur with a proven track record of success and innovation in marketing, sales, and cloud computing. Thanks to his study and practice of clinical psychology as a marriage and family therapist, he brings a unique perspective to the technology companies he has created. With his newest venture, RingDNA, Howard has combined his passion for the science of conversation with his expertise in revenue performance optimization. RingDNA is poised to transform the sales industry through integrated communications, data science, user-centric design, and optimized workflow.