Practical Strategies for Targeting the Fortune 1000

Editor's Notes

• #4: BAO recently conducted a research study of 208 Fortune 1000 enterprises to understand current budgeted initiatives, new technology adoption and purchasing trends. Demographics based targeting and it’s pitfalls Intelligence-based strategies for targeting right accounts at the right time Real world examples of how actual BAO Clients are using intelligence based targeting to go to market more effectively.
• #5: Budgeted strategic initiates in the Fortune 1000 Cloud checks in as the hottest budgeted initiative followed by Mobility/BYOD and business intelligence.
• #6: 20% of organizations - increasing IT budgets 18% - budgets decreasing. How much more targeted would your sales and marketing efforts be if you simply segmented your prospects into “those with increasing IT budgets and those with decreasing IT budgets “
• #7: The presence of Shadow IT could be a very meaningful data point. Gartner predicts that shadow IT will account for 35% of total IT spending in 2016. If we combine the lower two segments we see 32% of the Fortune 1000 engaging in some form of shadow purchasing which lines up closely with the Gartner prediction. BAO’s business mirrors this shift. Over the last few years we’ve seen a marked increase in clients targeting Line of business roles. 3 years ago we’d see maybe 10% of organizations using cross functional decisions making teams and 1% of organizations with LoBs free to purchase tech on their own. Now that combines number is up to 32%. ** note some orgs told us more than one of the three answers - hence the answers adding to a total greater than 100%.
• #8: 26% of Fortune 1000 organizations have cloud applications managed outside of IT Those that have chosen that strategy have invested heavily in it. BAO can pinpoint which organizations are actively engaging in shadow IT
• #9: Which lines of business are the Shadow IT “power users?” Operations, sales, marketing and finance. At an account level, this LOB insight can help dictate your account penetration plan
• #10: Software as a service is the most common usage of the cloud in the enterprise. 27% of organizations who are not using the cloud. Cloud adoption is an important identifier for many technologies; this data point alone could create major efficiencies
• #11: Almost two-thirds of Fortune 1000 companies are using big data within their organizations. 45% are using big data to analyze 1-2 areas of their business. Again, a trigger technology for many solutions, and rate of adoption can help you prioritize accounts.
• #12: The top uses of big data across the enterprise. operational analytics (35%), customer analytics (33%), and marketing analytics (30%)
• #13: If we were working with your organization on a specific technology we’d go a level deeper around that solution. Flash storage adoption is an example. 1/3 of the market has not adopted flash storage technology. Another third of the market has adopted flash but not heavily, less than 10% in fact, of that organizations overall storage environment.
• #14: 10% of organizations consider <15% of their storage data as mission critical. 46% of organizations consider 16-45% of their storage data as mission critical. 44% of organizations consider >46% of their storage data as mission critical.
• #15: Demographic data is publically available and easy to understand – is typically how accounts are identified and prioritized The Fortune 1000 is a very popular target market for obvious reasons Even the Fortune 1000 is not immune to the pitfalls of demographics based targeting. Your Total Addressable Market may be relatively static, but your actual target market should be constantly changing
• #16:   Demographic data to find lookalikes mimicking a big customer win Finding lookalikes isn’t as easy as a look-up in Hoovers
• #17: From the outside Polo Ralph Lauren looks demographically similar to Philips Van Heusen.
• #18: From an account-level perspective: A little color here, PVH currently appears on 49 client lists that we’re calling on. Polo currently appears on 22 of our client lists.
• #19: PVH doesn’t look like Polo Ralph Lauren at all. Baxter Healthcare & Nike. It’s now are they a good target or not. It’s are they a good target RIGHT NOW!
• #20: If you sell BI - Polo and Nike.
• #21: Data center overhaul – a common key trigger event for many tech solutions If you’re creating ABM campaigns, focus on Baxter and Polo And, from the sales side, if you’re an RVP New York could be doubling down your resources on Polo, and spending minimum time on PVH.
• #22: Selling cloud solutions –you should be focusing on PVH and Nike.
• #23: It’s not a question of, are a certain organization a good target or not. Are they a good target RIGHT NOW! Here’s a proportional sampling of logos from organizations in the fortune 1000 w/ budgeted IT projects
• #24: If you sell cloud solutions, this is your target market.
• #25: If you sell business intelligence software, this is your target market.
• #26: If you sell BYOD software, this is your target market.
• #27: Big data, data center overhaul and converged infrastructure.
• #28: ABM = lots of talk Client examples - what you can actually do with this type of strategy when you get back to your desk.
• #29: 21% had active initiative to purchase a new collaboration solution 28% rated current collaboration vendor as a C or below That market became a very important 367 companies Identified other trigger events, including length of tenure of CIO
• #30: 12% of market had active initiatives for a new anti-virus software 32% market were in last 12 months of current contract Key was to decrease wasted resources on accounts that weren’t likely to buy
• #31: Focus based on data that’s meaningful to your sales and marketing efforts 100% CUSTOMIZABLE, to your organizations needs. This process is fast We can do this into any market you want. BAO clients are using it to isolate data that’s meaningful to their sales and marketing efforts at an account level like, IT environment characteristics Competitive displacement opportunities Specific trigger events like finding a competitors’ expiring contracts Prioritize greenfield accounts
• #32: In addition to the raw data and contact info, we provide summaries to share with your organization internally An infographic like snapshot of the project highlights.
• #33: Page 2
• #34: For more info, download the Fortune 1000 trend report that we recently published A special offer for all attendees of today’s webinar Purchase an OppID project by July 1st and get 100 profiles for $15K A savings of $5000.