There is a great article on Politico, How Trump Let Himself Get Out-Organized, that explains how Trump’s Iowa debacle was a result of a failed analytics strategy. Trump made the same mistake many companies commit, he felt a strong brand and what he believe compelling product allowed him to under-invest in analytics. This issue was compounded by the aggressive use of analytics by competitors. Although this occurred in the political arena, there are lessons for all businesses.
The article explains that despite Trump’s strength in the polls, he did not have “the tools they needed, which is why they overpromised and underperformed.”
Penny wise and pound foolish
While Ted Cruz and Marco Rubio spent millions building sophisticated voter targeting machines, Trump did not start building a data operation to target voters until mid-October. It did not even start buying data (i.e. voter lists, etc) until November and waited to December to start using the Republican National Committee’s (RNC’s) voter file.
The Trump campaign declined to use Cambridge Analytica, a behavioral modeling company with political expertise, due to cost. Cruz, however, retained Cambridge Analytica’s services and the firm is now widely credited with engineering Cruz’s cutting-edge targeting operation. Rubio, who also over delivered on expectations, spent $750,000 for an outside company to assist in its data operations. Trump overall spent $560,000 on data services in 2015, compared to $3.6 million by the Cruz campaign. It is also about $700,000 less than Trump spent on hats.
You also need the analytics team
The Iowa caucas also showed the value of having a strong analytics team, not simply software. Cruz’s data team, which they call the Oorlog (the Afrikaner word for ‘war’) project, includes four full-time data scientists and embedded talent from Cambridge Analytics.
The Rubio campaign, which also exceeded expectations, has also invested heavily in its analytics team. It has a 22-person data war room in DC.
The Cruz campaign also hired ten canvassers (and recruited many volunteers) to go door-to-door to contact people the analytics suggested were supportive or could be persuaded. Traditionally, these so-called match rate initiatives are 50 percent successful but with Cruz’s advanced analytics the success rate reached 70 percent. The Cruz campaign also used the voter profiles to shape its strategies for most marketing activities, from television ad buys to telephone banks.
Micro-segmentation
Micro-segmentation, or creating very small customer segments and treating them uniquely, is another area where Trump fell down compared to Cruz. As Politico wrote, the Cruz campaign, “built a list of more than 9,000 Iowans who were still on the fence between their candidate and Trump. The team divided the undecided voters ― who were heavily evangelical and 91 percent male ― into more than 150 different subgroups based off ideology, religion and personality type, Wilson said. It used Facebook experiments to determine which issues jazzed up their voters the most.”
The lesson
No matter how strong you feel your product is, or how well it has performed in the past, you are vulnerable to competitors who may have a superior analytics solution. To combat this risk, you not only need to match the investment your competitor’s are making in analytics and look at micro-segmentation but also build a world class data team.
Key Takeaways
- Donald Trump’s loss to Ted Cruz in Iowa can be attributed to Cruz’s superior use of analytics to build a competitive advantage.
- Cruz invested much more in both analytic products and a great data team and it helped him get pro-Cruz people to caucus.
- Cruz also did a great job of micro-segmenting potential voters into more than 150 different subgroups based off ideology, religion and personality type and used Facebook experiments to determine which issues were most relevant for each subgroup.
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