Why Graph Search Is Facebook’s Big Data Solution March 05, 2013
The Cost Of Too Much Data May 21, 2013
Marketing Fail: When Tech Does More Harm Than Good November 14, 2013
Predictive Analytics in Marketing: Customer ESP September 24, 2013
Customer Marketing: The Opportunity Most Marketers Miss April 22, 2014
Why The Time is Ripe for Predictive Marketing April 16, 2014
A #MKTGnerd’s Guide to #MKTGnation14 March 31, 2014
- scott curtis
- customer advisory board
- sales challenges
- cliffnotes for bankers
- nick miller
- andy shefsky
- sports analogy
- company culture
- big data for marketing
- vander ark
- account based marketing
- morgan stanley smith barney
- marketing analysis
- steven miyao
What Do Online Dating And Sales Have In Common?
Predictions for 2013: The Growing Need For Sales Compatibility
Editor’s Note: In the coming weeks, we will release Predictions 2013: What’s In Store For Sales, Marketing and Big Data In 2013? The ebook features predictions from over 20 industry thought leaders. Here is a prediction from Andrew Gaffney, Editor of DemandGen Report. Check back next week for a prediction from Jonathan Farrington of Jonathan Farrington and Associated.
Recent research shows that spending on online dating sites grew by more than 60% last year, in yet another sign that that people are increasingly comfortable trusting the fate of their relationships to the digital domain.
This trend is telling for sales teams because it underscores that even when people are shopping for the person they may spend the rest of their lives with, they see the value that business intelligence and analytics can provide. By using the intelligence gathered through online quizzes, these sites use advanced algorithms to match people based on hobbies, interests and preferences.
These capabilities are also becoming common in online shopping experiences where recommendation engines and personalization tools offer consumers suggestions on other products they would likely be interested in purchasing.
The transformation in how people connect and engage on a daily basis is quickly migrating into the business world, reducing the effectiveness and tolerance for cold calls and blast emails.
Whether they are considering a new TV for their home or a new phone system for their business, buyers are expecting and demanding that sales people start the conversation with some intelligence about them and deliver targeted and relevant offers based on that knowledge.
The 2012 B2B Buyer Survey conducted by DemandGen Report showed more buyers are turning to social media, websites and peers to research solution providers before they even engage.
Buyers are realizing the value of showing up for a meeting with a provider as informed as possible to see if there is a fit for a long-term relationship, and they are expecting that sales people have done the same homework.
In fact, buyers we surveyed ranked “relevance of information the company provided based on my questions” as the most important factor influencing their vendor selection.
This growing expectation of relevance and intelligence is changing the game for sales teams. Rather than relying on relationships and sales tactics, those teams that utilize sales intelligence and access the right data from social media and other channels will have a decided advantage over their competitors.
Another trend making sales intelligence and data a necessity for sales teams is the fact that much of the traditional sales cycle is taking place without any sales involvement. Our survey found 51% of buyers said they didn’t interact with a representative until after they had established a preferred list of vendors and 13% didn’t engage until after they had put out RFPs or were ready to negotiate pricing terms.
By this point, sales teams are working at a disadvantage and intelligence on the key pain points and areas of interest of a prospect are often the tools that can get teams back in a deal that would have been lost.