This will puncture the myth that Murrell was a strategic genius

Jan 2017: Use of Gathered Data – Analysis of Petition Outcome

I compiled an analysis using information available to the public and produced a predictive 2017 election outcome.

Electorate totals were included and a percentage signatory total was established for each constituency. From that I used the mean figure of 3.75% to forward project the outcome of an Independence referendum.

The figures suggested that from an electorate of 4,021,203 the outcome of another referendum would result in a: 48.00% “Yes” vote in favour of independence with 52.00% preferring to remain with the Union. 

This was important information which if used wisely would allow effective forward planning electioneering strategy.

As expected Edinburgh, Aberdeen, East Renfrewshire and East Dunbartonshire recorded higher than average figures favouring remaining with the Union.

SNP's Mr Invisible may be taking the flak from dissidents, but critics are  also targeting his wife

Jan 2017 General Election Calton Jock forecast 

The General Election in Scotland will not be a re-run of the 2015 General Election and the landslide victory achieved by the SNP cannot realistically be achieved.

My analysis suggests 25 seats might be lost to the Tory Party.

Significant SNP financial resources and additional teams of activists will need to be deployed in force in the under-noted constituencies otherwise they may be lost.

This group of seats are marginals – risk decreases as the % number drops:

71749: Edinburgh West, Michelle Thomson MP : 4388-6.12% Lost

69982: East Renfrewshire, Kirsten Oswald MP: 4241-6.06% Lost

66966: East Dunbartonshire, John Nicolson MP: 3977-5.94% Lost

73445: West Abdn, Stuart Blair Donaldson MP: 3961-5.40% Lost

80978: Edinburgh North & Leith, Deidre Brock MP: 4280-5.29% Held

66208: Paisley & Renfrew, Gavin Newlands MP: 3158-4.77% Held

68875: Argyll & Bute, Brendan O’Hara MP: 3277-4.75% Held

62003: North East Fife, Stephen Gethins MP: 2937-4.74% Held

67236: Stirling, Steven Paterson MP: 3175-4.72% Lost

77379: Ochil & Perth, Tasmina-A-Sheikh MP: 3645-4.71% Lost

79393: Gordon, Rt. Hon Alex Salmond MP: 3711-4.68% Lost

68056: Aberdeen South, Callum McCaig MP: 3618-4.65% Lost

79481: East Lothian, George Kerevan MP: 3676-4.63% Lost

72178: Edinburgh S-West, Joanna Cherry QC: 3283-4.55% ) Held

72447: Perth & N-Perthshire, Pete Wishart MP: 3033-4.19% Held

71685: Moray, Rt. Hon Angus Robertson MP: 2995-4.18% Lost

78037: Lanark & Hamilton-E, Angela Crawley MP: 3272-4.19% Held

74179: Berwick, Roxburgh, Selkirk: Calum Kerr MP: 3026-4.08% Lost

86955: Linlithgow, East Falkirk, Martyn Day MP:3570-4.11% Held

68609: Banff & Buchan, Dr Eilidh Whiteford MP: 2772-4.04% Lost

73445: W. Abdn,  Stuart-B-Donaldson MP: 3961-5.40% Lost

71685: Moray, Rt. Hon Angus Robertson MP: 2995-4.18% Lost

68056: Aberdeen South, Callum McCaig MP: 3618-4.65% Lost

Revealed: The secretive SNP chieftains helping Alex Salmond break up the  Union | Daily Mail Online

The 2017 General Election and the resurgence of the Tory Party in Scotland

The 2017 General Election in Scotland first exposed Scottish voters to “data mining”. A new form of politics imported from the USA, providing tools and profiling information allowing Tory candidates to communicate personally with their prospective constituents.

The benefits were astounding. The Tories gained a stunning result, increasing their MP’s from 1 to 13 in total.

Pollsters were flabbergasted at the turnaround in the voting since the SNP appeared to be invulnerable.

But Tory candidates had been well briefed about the individual targets within their constituencies. The new voting strategy used predictive data models which identified, engaged and persuaded swing voters to turnout.

This was achieved through the use of internet, phone and personal surveys combined with many other data sets, created by teams of contracted data scientists, psychologists and political consultants allowing the campaign to map the Scottish electorate based on ideology, demographics, religious beliefs, strongly held opinions on key issues e.g. Independence, the Orange Lodge, Celtic, Rangers, The SNP and or political personalities.

The information gathered provided Tory campaign strategists with a predictive analysis based on thousands of data points on just about every voter in Scotland.

From that teams of political consultants and psychologists, hired by the Party directed the campaign and candidates on what and how to say it to selected groups of voters.

Other voter targeting, included use of Facebook adverts, one to one scripted phone calls and provision of the content of messages for door-to-door canvassers ensuring consistent communication with voters on any issue.

What won the day for the Tory party in 2017 was that they utilised “data mining” to gain a comprehensive understanding of the Scottish electorate and then used every communication aid available facilitating discussions with voters about matters important to them as individuals.

Throughout the campaign the Tory tactic was to constantly broadcast the “no new referendum” message in the “no” constituencies stressing the major difference between the Tory and any other candidates firmly imprinting this in the electorate’s minds.

In contrast the SNP campaign lacked inspiration. It was poorly directed (Murrell deliberately starved “at risk” constituencies of financial and other resources) and failed to get the SNP voters out.

Information is power and the incompetent SNP strategist, Peter Murrell, was outwitted by the Tory Party.

Had he been the chief strategist of any political party other than the SNP he would have been given his marching orders.

Incredulously the First Minister, (his wife) awarded him a massive pay rise and an extended contract.


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