Asia-Pacific Broadcasting (APB) June 2018 Volume 35, Issue 5 - Page 23

23 MANAGEMENT June 2018 ❝ What is needed, is a holistic view across digital that is comparable and unduplicated with linear media, in order to understand the impact of programming and advertising on the big and small screens. ❞ — Craig Johnson, Managing Director, Media, Nielsen measurement across all devices and platforms. This, in turn, deliv- ers un duplicated and comparable metrics from an independent au- dience measurement solution, and offers a view of what people watch across devices and platforms. Johnson continues: “The flex- ibility of the framework allows clients to leverage components for linear and dynamic content for both programming and ad- vertising, as well as cross-platform content analysis insights. “Within the Total Audience framework, Nielsen has also devel- oped Digital Ad Rating (DAR) and Digital Content Ratings (DCR) to measure in conjunction with linear TV audience measurement.” He also believes that because broadcasters are today faced with the challenge of combining digital and traditional media, having multiple sets of metrics is counter- productive. “What is needed is a holistic view across digital that is comparable and unduplicated with linear media, in order to under- stand the impact of programming and advertising on the big and small screens.” Comparable metrics, says Johnson, allow broadcasters to un- derstand how audiences interact across their various platforms and accordingly, adjust demographics and programme durations to at- tract maximum audience reach across all devices. Unduplicated reach metrics across all platforms and devices is key, he emphasises, while suggest- ing that this “unduplicated reach” should form the building blocks for all other metrics. “It is important to all broadcasters and advertis- ers that the metrics produced are comparable and can be used from planning to post analysis. “Return on investment (ROI) is emerging as the most important measure — this is why Nielsen has a strategy of measuring Reach, Resonance and Reaction,” Johnson concludes. In an increasingly digitised world, the continued emergence of disruptive technologies should perhaps not be seen as a surprise. Artificial intelligence (AI), for in- stance, is projected by Gartner to produce US$1.2 trillion worth of global business value by this year alone — an amount that will more than triple to $3.9 trillion in 2022. Where audience measure- ment and analysis is concerned, AI will appear to fit like a glove; machine learning and increasing auto mation are poised to offer broadcasters insights into their audiences the likes of which they have not experienced before. This, in turn, will allow them to target specific content and advertising campaigns to audiences who are most likely to be receptive. Businesses operating in today’s environment need to provide products or solutions that meet the needs of real people, says Nielsen’s Johnson. The problem is — people are constantly changing, compel- ling brands to stay relevant in or- der to attract new customers, while having to simultaneously increase loyalty among current customers. “Adapting to all these changes has never been more difficult, consid- ering the staggering amount of big data to organise, understand and act on,” Johnson adds. To address these issues, Niels- en has created an adaptive learning technology – Nielsen Artificial Intelligence (Nielsen AI) – that is built into the Nielsen Marketing Cloud (NMC), and which auto- mates FR7&VFBF֗6ЧFbVFV6RFV2( F0Wr6&ƗGV&W26ƖVG2F&W7B7FFǒF&VFP6vW267VW"&VfW"&W7VFr&R&VWfB6FV@BGfW'F6rvW"WfV2`7W7FW"VvvVVBBЧ&fVB$( 626f"VF6'B&rFF&R&VG'BbG2&F@FRVwW&$ttU2&rFFB'Ff6FVƖvV6Rv&G0VB7BFV6V&W"rrFR$R6FVBǗF726RЧF6Ɩ6VBFRF6F2f ( W6VV6RFFǗF7>( @( W6VV6RFFG&fV'W6ЦW72&6W72Vff6V7( GvWB`ffRv&G26FVv&W2&W6VFVB( ĖW'f6fVǒFvFBЧ66RvR6VRFV6w27&F6'BbVFV6RV7W&RЦVB( 6&W2VF6'( 26v( 2VFFf&6vR6V7B&V2bFFWfW'FEvRVVBFWfW&vPB&rFFFV6vW2FR&WGFW"6V6RbFRFF@F&fR6vG2B7VVBFЦ&WB( Ф&%Eb'&w2&RVff6V7FVFV6RV7W&VV@vW&R6RVFV6RV7W&VVBffVB'&B( 66GFW&wV&6( f"g&VRF"eDWGv&2B2r&fVBB6vV@6vf6FǒFFRW6RbG'VRǗF72f"fW"ЧFRFEB6W'f6W27VvvW7FVBFfB&6WGBvVW&vW"vw&WआRFB#( Ćfr6BFBFRG&FFЦFW'&W7G&WGv&>( VFV6RV7W&VV@F2fRB&VǒGf6VBFw&VFǒFPFVw&FbFRFW&WBvWfW"6vV@WfW'FrFRƖRv&BW7V6ǒvF'&B'&F67B'&F&BEb&%Eb( FRW6֖rE4227FF&Bv67GW&R$r4DFFvfVf&6'FFfWvW"WBWRvfVf&$r4DGFW"WFW'2$r4DFFfWpGFW"7Fw&GFW"7V7G'V6&RfWpvgW'FW"FVw&FrFRFW&WBF6ЧFVBFVƗfW'BFBvGW&6ffV7@VFV6RV7W&VVBFV6VW2BF2( ФFRVFR&6WGBGf6VB'&BЦ67FW'2F6FVRFrvBFV"fWvW'0&RvF6r( BFW&2b6FVBvV&RprFW&RvF6rBvBFWf6RFW&RvF6rFW6RWWG&726FV&PW6VBF'VB67W&FRfWvW"&fRBЦr'&F67FW'2FF&vWBFV"fWvW'2vFG'VP&w&&RGfW'F6rF7&V6R&WfVVR6FVRFF"&%Eb&V6W6RB6&RfV&RF&6WGBV66VB( Ć&%E`'&w2FRƖRv&BFFRƖV"v&BB7&VFW2G'VRBFvBֶB6VGvfVV'BbFR&w&֖rG6VbF02fW'VffV7FfRvb6V7FrVFV6W0B7&V6rFV"FW&7FfGvFFR&Цw&R2R6vWB&W76Rg&fWvW'0&VFR( ХF27&VFW2Gvv7G&VWB&WGvVVFP'&F67FW"BFRfWvW"BG2VffV7FfRЦW726&R67W&FVǒV7W&VBFFFǒ'&F67FW'26W6Rr֖2f66VFFf&2FV7&VFRBFWfVfWvW"G0B&fW2&6WGB66VFVBvw&W( 2FfB&6WGC( FRW6֖rE4227FF&BvvgW'FW"খFVw&FrFRFW&WBF6FVBFVƗfW'BFBvGW&6ffV7BVFV6PV7W&VVBFV6VW2@F2( ФWpF"𦐤@@c@VG&DF&Ǘ6W"vVW&F"6fW'FW FG&W76rFRVVG2bVf7GW&W'2vF$rǗ62vVW&Fb6fW'6VG&"4DDTBvfVf&&7FW&W VWFrFF( 2VVG2f"DTB&GV7F7B&GV7FBw&FrE"Bt4p4B$r4DǗ60GFW"WFW"7Fw&ЮGFW"vfVf&7V7G'VfW"s4DRf&G0D2&6VBWfVBvvpfFVVF0FFǗ62Ǘ62vVW&F4BBD6fW'F4WFF4BFD4BF$r4DզRDf6R6W vfVf&4RvW@fV7F'66R7Fw&Хr2r7W'@&VvbFW&W7@ƖRGFW&vVW&FD2&6VBWfVBvvpCrcbs40VFbVFW70F'WFFFbFV6FR4DR###"bwwrFVGb6W4FVGbCB#Sb3CRVG&E4D'&F67BvfVf&&7FW&W 7W'Fr'&F67B&GV7FVvVW&rWG6FR'&F67BW&F2B6G&&0gV27G'VVB6W@VFbVFW70Crcbs40D2&6VBWfVBvvpƖRGFW&vVW&F 4B4r4D27FF&@66W"Ǘ624DR###"bFFǗ62E"Gf6VB6W"F'WFFFbFV6FRWw&FV&RFTBTfƖ