{"id":4260,"date":"2019-03-27T12:19:15","date_gmt":"2019-03-27T16:19:15","guid":{"rendered":"https:\/\/acaweb.ca\/en\/?p=4260"},"modified":"2019-03-27T12:34:02","modified_gmt":"2019-03-27T16:34:02","slug":"dashboards-a-conversation-with-nick-drew-of-fuse-insights-and-sean-dixon-of-omnicom-media-group","status":"publish","type":"post","link":"https:\/\/acaweb.ca\/en\/2019\/dashboards-a-conversation-with-nick-drew-of-fuse-insights-and-sean-dixon-of-omnicom-media-group\/","title":{"rendered":"Dashboards: A conversation with Nick Drew of Fuse Insights and Sean Dixon of Omnicom Media Group"},"content":{"rendered":"

\"Dashboard\"<\/p>\n

    \n

    \t<\/p>\n

  1. What\u2019s the biggest challenge facing the marketer as they develop a dashboard?<\/li>\n

    <\/strong><\/p>\n

    Nick Drew:<\/strong> It\u2019s being drowned in data. As we said in the whitepaper, there is so much data available that could conceivably be relevant; and you can keep adding and adding, in a \u201coh, just this one more piece, because we might need it\u201d way until you end up with something utterly unworkable that doesn\u2019t do what\u2019s needed.
    \nThe other danger is related, and is being distracted by the data (or the visualization), big numbers often feel like the goal \u2013 \u201cthis number is bigger than that one, therefore it\u2019s better\u201d. The goal of the dashboard is to enable actionable insight and that might come from a mistake.<\/p>\n

    Sean Dixon:<\/strong> I agree, and think that it underscores the need for a plan. A dashboard should be a mechanism to evaluate your strategy. If you\u2019ve done the necessary step of identifying your top-level objective, every decision to include a metrics should flow from the top down. Without a Strategy, there\u2019s just too many metrics to choose from and you can lose sight of meaningful measurement.<\/p>\n

    \t<\/p>\n

  2. Give the listener one \u201cmust do\u201d or one \u201cdon\u2019t do\u201d<\/li>\n

    <\/strong><\/p>\n

    Nick Drew:<\/strong> You must start with a clear vision of why you\u2019re doing this \u2013 and not just a \u201cbecause we want to be smarter\u201d, but a clear objective, that \u201cthis dashboard will achieve ____; by showing us ____\u201d. That\u2019s your north star, essentially, as you build the dashboard, and as you consider which metrics to include, what to do with them etc. And you\u2019ll probably find you come back to it over time; it\u2019s a good way to assess whether your dashboard is good enough, by questioning whether it\u2019s hitting that objective.
    \nAnd you mustn\u2019t start by imagining that the data will show you the right dashboard to build \u2013 you have to bludgeon the data into submission!!<\/p>\n

    Sean Dixon:<\/strong> I guess we won\u2019t have too much in the way of opposing viewpoints. I might add\/repeat design before you build, not after.<\/p>\n

    \t<\/p>\n

  3. Do people have a pretty good understanding of where the numbers come from and their definitions?<\/li>\n

    <\/strong><\/p>\n

    Nick Drew:<\/strong> I think my answer would be \u201cit depends\u201d, but that it\u2019s also important to understand how much you need to know. Do you need to know the exact panel size comScore has \u2013 probably not. But do you need to know the potential biases and how to compare impression counts from Facebook with MOAT figures \u2013 absolutely.<\/p>\n

    There are two main points where this is a vital question. The first is looking at the data you need versus the data you actually have, and trying to fit the latter into your vision At that point, you really need to understand what the number means so that something isn\u2019t lost in translation. <\/p>\n

    The second is when comparing two sources for what seems like the same proof point, for instance comparing impressions from a platform versus impressions from 3rd party ad verification from the same campaign. Whether a number is \u201cright\u201d or \u201cwrong\u201d is somewhat moot at this point \u2013 what\u2019s more important is whether they\u2019re right or wrong for what you need. Sean made a really good point that a platform\u2019s numbers can be 100% correct but still be pointless for you \u2013 it\u2019s simply showing how many impressions you paid for, not how many people saw them, or how many were interacted with. Again, knowing what the numbers show, and what they mean, is vital here.<\/p>\n

    \t<\/p>\n

  4. Is attribution modelling too short term focused?<\/li>\n

    <\/strong><\/p>\n

    Sean Dixon:<\/strong> Attribution modeling always includes some amount of assumptions, whether that\u2019s in the nature of the data, the tactic or thing being measured, or even model fitting. As long as those assumptions are considered, adding context to model outputs, the time frame for attribution modeling should be appropriate to those limitations. For an overall business view, yes, I think the focus on MTA and immediate or near-term decisions around MMM & MTA does tend towards being too short term.<\/p>\n

    \t<\/p>\n

  5. Is market mix modelling too cumbersome?<\/li>\n

    <\/strong><\/p>\n

    Nick Drew:<\/strong> It is very cumbersome \u2013 particularly in the gathering of data over the required period. It\u2019s limited in what it achieves: it isn\u2019t a silver bullet that magically tells you what mix to use, and it\u2019s totally built on what\u2019s happened before (it\u2019s not a guarantee of what will happen in the future). And it\u2019s expensive. But it also provides a level of insight and guidance at a macro level that can\u2019t really be achieved with current tech through other means.<\/p>\n

    Sean Dixon:<\/strong> Totally agree again. There\u2019s also the issue of how reductive the modeling has to be. It can scale up through nested models, sure, but so much of the strategy and nuance of the roles of media, different objectives, etc. has to be boiled down to dollars or impressions, and when MMM is modeled against outputs that weren\u2019t campaign objectives, there\u2019s real risk using MMM as the gospel as to how your budget should be allocated. As Nick mentioned, it\u2019s always looking back, and external factors can really disrupt the findings when applied moving forward. There\u2019s tremendous value in MMM, it can help justify spends and depending on the scale and complexity, demonstrate the impact certain variables have on business goals, but it\u2019s an ingredient in effective advertising, not the whole recipe.<\/p>\n

    \t<\/p>\n

  6. Why do dashboards fail?<\/li>\n

    <\/strong><\/p>\n

    Nick Drew:<\/strong> Scope creep and\/ or imperfect scope definition. When you have a clearly defined framework of \u201cthis dashboard will\u2026. By showing \u2026.\u201d, it\u2019s relatively straightforward to build and maintain to those specs \u2013 even making the necessary compromises. A vague start, or trying to add elements along the way, while not a surefire recipe for disaster, reduces the efficacy of the dashboard, and its relevance.<\/p>\n

    Sean Dixon:<\/strong> Dashboards are a platform for insight. Presenting information that doesn\u2019t provide for insight and action makes it irrelevant and frustrating. Action comes from making them part of workday as status controls, holding responsibility, uncovering mistakes to reflect upon and celebrating team milestones. One big question is who gets to see the dashboard?<\/p>\n

    \t<\/p>\n

  7. The focus on short term metrics has been blamed for brand destruction, are real time dashboards to blame?<\/li>\n

    <\/strong><\/p>\n

    Nick Drew:<\/strong> Marketing theory is important, and as Byron Sharp puts it, balancing the right funding ration between branding vs response-led campaigns should not be overlooked. It\u2019s vital context as you map out brand objectives, what you need from a campaign, and over how long a timescale you should be judging success. That influences what\u2019s on brand dashboard and what\u2019s on the response dashboard.<\/p>\n<\/ol>\n

    Download The Marketer\u2019s Guide to Dashboards<\/a>
    \n<\/p>\n

    *You must be an ACA member to access this content.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

    What\u2019s the biggest challenge facing the marketer as they develop a dashboard? Nick Drew: It\u2019s being drowned in data. As we said in the whitepaper, there is so much data available that could conceivably be relevant; and you can keep adding and adding, in a \u201coh, just this one more piece, because we might need […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"categories":[127,185,193],"tags":[838,839,837],"acf":[],"yoast_head":"\nDashboards: A conversation with Nick Drew of Fuse Insights and Sean Dixon of Omnicom Media Group | Association of Canadian Advertisers<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/acaweb.ca\/en\/2019\/dashboards-a-conversation-with-nick-drew-of-fuse-insights-and-sean-dixon-of-omnicom-media-group\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Dashboards: A conversation with Nick Drew of Fuse Insights and Sean Dixon of Omnicom Media Group | Association of Canadian Advertisers\" \/>\n<meta property=\"og:description\" content=\"What\u2019s the biggest challenge facing the marketer as they develop a dashboard? 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