tag:econsultancy.com,2008:/topics/data-analytics Latest Data & Analytics content from Econsultancy 2017-02-21T01:00:00+00:00 tag:econsultancy.com,2008:BlogPost/68822 2017-02-21T01:00:00+00:00 2017-02-21T01:00:00+00:00 Where is data-driven marketing headed in 2017? Jeff Rajeck <p>Terms like programmatic buying, real-time bidding (RTB), data management platform (DMP), customer data platform (CDP), and attribution modeling are now standard lingo when talking about using data for marketing nowadays. Without some grasp of these terms and the concepts behind them, marketers can quickly become lost when speaking with others in the biz. </p> <p>Perhaps, then, it does make sense to talk about 'data-driven' marketing differently from other marketing which focuses more on the '<a href="https://en.wikipedia.org/wiki/Marketing_mix">four Ps</a>' or '<a href="https://econsultancy.com/blog/67395-three-things-email-marketing-leaders-do-regularly-apac-case-studies/">STP marketing</a>'.</p> <p>For readers who feel that they need to catch up in this area, Econsultancy has a <a href="https://econsultancy.com/blog/65677-a-super-accessible-beginner-s-guide-to-programmatic-buying-and-rtb/">number of blog posts</a> on <a href="https://econsultancy.com/blog/67583-what-does-the-future-hold-for-data-management-platforms/">these topics</a> and Econsultancy subscribers can consult our recent research covering <a href="https://econsultancy.com/reports/the-cmo-s-guide-to-programmatic">programmatic</a>, <a href="https://econsultancy.com/admin/blog_posts/new/%20https:/econsultancy.com/reports/programmatic-branding">data-driven branding</a> and the <a href="https://econsultancy.com/reports/the-role-of-crm-in-data-driven-marketing">role of the CRM in data-driven marketing</a>.</p> <p><img src="https://assets.econsultancy.com/images/0008/3993/cmo_guide_to_prorammatic_-_old_template-report-full.jpg" alt="" width="800" height="594"></p> <p>But for those who are familiar with these concepts, the next question is: where is it all headed? What changes should marketers anticipate in 2017 with regards to the technology, capabilities, and effectiveness of data-driven marketing?</p> <p>To find out more on this topic, we interviewed an industry expert, Will Griffith from Oracle Marketing Cloud, who offers three big ideas about data-driven marketing in the video below, followed by some commentary on his points.</p> <p><iframe src="https://www.youtube.com/embed/bwXSj5Ws-yM?wmode=transparent" width="560" height="315"></iframe></p> <h3>1. Platforms, technology, and data are improving</h3> <p>Using data to buy media and place creative can be frightening. It cedes control of ad buying, site choice, and audience targeting to an algorithm which may lead to both <a href="https://econsultancy.com/blog/67659-three-things-that-show-the-scale-of-the-ad-fraud-challenge/">ad fraud</a> and <a href="http://www.thetimes.co.uk/article/big-brands-fund-terror-knnxfgb98">inappropriate placements</a>, both of which may harm a brand. </p> <p>These concerns are part of the reason why, as of late 2015, more than half (57%) brands <a href="http://digiday.com/brands/5-charts-brands-publishers-using-dmps-globally/">have not yet implemented a DMP</a> and most (61%) were not going to implement one in the coming year.</p> <p><img src="https://assets.econsultancy.com/images/0008/3994/plans-.jpg" alt="" width="800" height="441"></p> <p>What may alter this trend, however, is that marketers are becoming increasingly aware of the data-driven platforms and technology that is available and realize that they are improving.</p> <p>Facebook and Google are leading the way in making data available to advertisers. Programmatic ad-buyers on these and other demand-side platforms (DSPs) can now choose to pay by impression, click, action, download or a number of other different metrics. These platform and technology improvements then lead to better data about consumer interests which, in turn, make the platforms more valuable.</p> <p>As Mr Griffith points out in the video, all of these improvements lead to new opportunities for brands who are able to devise new strategies which use the new technologies. </p> <h3>2. Marketers are increasingly using data to improve performance</h3> <p>Along with catering for new marketing strategies, the improvements in platforms, technology and data also help marketers understand what is and what is not working. This allows brands, as Mr Griffith points out, to understand what they are getting for their media spend as well as understanding how to improve the customer experience once people are on their site.</p> <p>According to a recent Econsultancy survey, the two most popular methods for improving conversion rates derive from data, customer journey analysis and A/B testing.</p> <p><img src="https://assets.econsultancy.com/images/0008/3995/conversion.jpg" alt="" width="800" height="531"></p> <p>Additionally, the most popular place for marketers to get ideas for what to test comes from analysing data.</p> <p><img src="https://assets.econsultancy.com/images/0008/3996/testing.png" alt="" width="800" height="489"></p> <p>This means that in order for their brands to remain competitive, marketers need to use data to both review the performance of their campaigns as well as guide changes to their marketing, customer journey, and digital properties.</p> <h3>3. Through combining first- and third-party data, marketers will be able to allocate budget more effectively</h3> <p>In the video, Mr Griffith alludes to the recent trend to combine first- and third-party customer data to improve marketing performance. While it sounds like a complicated strategy reserved for only those 43% of companies who have implemented a DMP, combining first- and third-party data is actually straightforward to do with the major advertising platforms.</p> <p>Google offers a facility where marketers can upload customer data and then target both display and search ads based on both the uploaded (first-party) and Google (third-party) data.</p> <p><img src="https://assets.econsultancy.com/images/0008/3997/google.jpg" alt="" width="800" height="415"></p> <p>Facebook offers similar capabilities and even lets you remove people from the list who do not meet your current targeting requirements.</p> <p><img src="https://assets.econsultancy.com/images/0008/3998/facebook.jpg" alt="" width="800" height="227"></p> <p>Additionally, all major ad platforms, DMPs and DSPs offer retargeting capabilities which let marketers use onsite behavior, such as a product view, to determine what ad is shown to a potential customer. Combined with contextual, interest, and in-market consumer data from third-party data providers and consumer targeting can become very sophisticated, indeed.</p> <p>Data-driven marketing has certainly come a long way from just measuring cost-per-click and bounce rates. Marketers now have a wide array of platforms, technology, and data sources to use which help them target the right consumers, improve marketing performance, and devise new strategies.</p> <p>The task ahead for marketers is to become familiar with what is now available to them or risk losing out in the digital realm to brands who have a more informed approach to data-driven marketing.</p> tag:econsultancy.com,2008:Report/4395 2017-02-06T10:00:00+00:00 2017-02-06T10:00:00+00:00 Healthcare and Pharmaceuticals Internet Statistics Compendium <p>Econsultancy's <strong>Healthcare and Pharmaceuticals Internet Statistics Compendium</strong> is a comprehensive collection of the most recent healthcare and pharma statistics and market data publicly available on online marketing, ecommerce, the internet and related digital media.</p> <p>The report will be <strong>updated twice a year</strong>.</p> <p>Like our main <a title="Internet Statistics Compendium" href="https://econsultancy.com/reports/internet-statistics-compendium">Internet Statistics Compendium</a>, this report has been collated from information available to the public, which we have aggregated together in one place to help you quickly find the healthcare and pharma internet statistics you need.</p> <p>There are all sorts of internet statistics which you can slot into your next presentation, report or client pitch.</p> <p>Areas covered in this report include:</p> <ul> <li>Digital healthcare market trends</li> <li>Consumer internet and mobile usage</li> <li>Digital health investment / funding</li> <li>Digital strategy</li> <li>Internet of Things (IoT) and wearables</li> <li>Online pharmacies</li> </ul> <p><strong>A free sample document is available for download.</strong></p> tag:econsultancy.com,2008:Report/4388 2017-02-02T14:00:00+00:00 2017-02-02T14:00:00+00:00 Digital Intelligence Briefing: 2017 Digital Trends <p>The <strong>2017 Digital Trends</strong> report, based on the seventh annual trends survey conducted by Econsultancy and <strong><a title="Adobe" href="http://www.adobe.com/marketing-cloud.html">Adobe</a></strong>, highlights the key digital trends, challenges and opportunities which marketers need to be aware of during 2017, covering topics ranging from customer experience and mobile to data-driven marketing and personalisation.</p> <p>The 2017 edition of this research also investigates how committed organisations are to digital transformation, which is intrinsically linked to creating a great customer experience.</p> <p>The report is based on a global survey of more than 14,000 marketers and ecommerce professionals carried out at the end of 2016.</p> <h3>The following sections are featured in the report:</h3> <ul> <li>The hard realities of digital transformation</li> <li>Looking back on 2016</li> <li>Priorities and budget plans for 2017</li> <li>Keeping up with customer expectations</li> <li>Building a digital culture</li> <li>Design-driven transformation</li> <li>Looking forward to the future</li> <li>Fit for the future: three key areas marketers should focus on</li> </ul> <h3> <strong>Findings</strong> include:</h3> <ul> <li>Over one fifth (22%) of client-side respondents ranked<strong> 'optimising the customer experience' </strong>as the single most exciting opportunity for the year ahead, slightly ahead of other areas such as 'creating compelling content for digital experiences' (16%) and 'data-driven marketing' (12%).</li> <li>The <strong>priorities</strong> that sit atop marketers’ lists are content marketing (29%), social media engagement (28%) and targeting and personalisation (25%).</li> <li> <strong>Design </strong>is considered the next level on the path to digital transformation, with 86% of survey respondents agreeing that design-driven companies outperform other businesses.</li> <li>While over four-fifths (82%) of survey respondents believe that <strong>creativity</strong> is highly valued within their organisations and around three-quarters (77%) are investing in design to differentiate their brand, just over two-fifths (44%) don’t think that they have the processes and collaborative workflows to achieve a design advantage.</li> <li>A key part of delivering differentiated customer experiences in the future will involve looking beyond mobile and focusing on <strong>the Internet of Things (IoT), augmented reality (AR) and virtual reality (VR)</strong>, channels which are regarded by survey respondents as exciting prospects over the coming years.</li> </ul> <p><strong>Econsultancy's Quarterly Digital Intelligence Briefings, sponsored by <a title="Adobe" href="http://www.adobe.com/marketing-cloud.html">Adobe</a>, look at some of the most important trends affecting the marketing landscape. </strong><strong>You can access the other reports in this series <a title="Econsultancy / Adobe Quarterly Digital Intelligence Briefings" href="http://econsultancy.com/reports/quarterly-digital-intelligence-briefing">here</a>.</strong></p> tag:econsultancy.com,2008:BlogPost/68727 2017-01-20T14:14:00+00:00 2017-01-20T14:14:00+00:00 10 of the best digital marketing stats we’ve seen this week Nikki Gilliland <p>Don’t forget, you can download the <a href="https://econsultancy.com/reports/internet-statistics-compendium" target="_blank">Internet Statistics Compendium</a> for lots more insight.</p> <p>On we go...</p> <h3>Less than half of consumers satisfied with retail apps</h3> <p>New research from Apadmi has found that retail apps are failing to meet the expectations of consumers, with just 40% of UK consumers being satisfied with the apps they’ve downloaded in the past.</p> <p>Nearly one in five say they would like retailers to invest more heavily in improving apps, while 30% would be more likely to use them if they had a wider range of features. </p> <p>Lastly, 25% of consumers say they would think less of a retailer that failed to update its app regularly.</p> <h3>Online searches for food trends increase</h3> <p>New data from Hitwise has revealed that online searches related to diet, nutrition and super-food have risen by 70% in the past two years. Searches for ‘gluten-free’ have become particular popular, rising 141% since 2014. </p> <p>Meanwhile, searches for ‘paleo’ enjoyed a big spike at the start of 2016, however with New Year’s resolutions waning, interest declined as the months passed.</p> <p><img src="https://assets.econsultancy.com/images/0008/3234/Gluten_Free_Searches.png" alt="" width="624" height="310"></p> <h3>92% of online consumers don’t intend to buy during a first visit </h3> <p>A new report by Episerver has discovered that too much of a focus on conversion means retailers could be missing out on opportunities for engagement.</p> <p>In a survey of over 1,000 consumers, it was found that 92% who visit an ecommerce website or mobile app with the intent of buying rarely or never complete checkout.</p> <p>This reflects the importance of relevant and engaging content that supports the entire purchase journey, rather than content that's geared around getting consumers to buy.</p> <h3>Location &amp; convenience drives supermarket shoppers </h3> <p>Despite continual ‘price wars’ between the big four supermarkets, consumers don’t choose where to shop based on low prices - this is according to a new study by TCC.</p> <p>In a survey of 1,530 UK shoppers, proximity and location was found to have the biggest influence on where consumers shop, with 48% of Brits citing this as the main factor. </p> <p>40% of survey respondents said a decent range of products and services, 39% said habit and familiarity, while just 34% said low prices. </p> <p><img src="https://assets.econsultancy.com/images/0008/3243/sainsburys.jpg" alt="" width="650" height="433"></p> <h3>Half of students predict online tracking would improve grades</h3> <p>According to new research by Kortext, 47% of students believe that they would achieve better grades if their lecturers were able to track their study habits throughout the academic year.</p> <p>In a survey of over 1,000 current and former students, 91% said they would be happy for universities to use analytics to track weekly progress, while 76% said that a closer monitoring of study habits would lead to fewer university dropouts.</p> <h3>Over 50s spend 71% more per visit than younger shoppers</h3> <p>Coniq has found that shoppers over the age of 50 tend to spend 71% more in shopping centres than younger people, despite visiting 25% less.</p> <p>The research also found that the over 50s complete around 45% of transactions per trip, which is a much higher amount compared to other consumer age groups. Likewise, older consumers were found to make use of 31% more offers than younger age demographics.</p> <p>For retailers, this proves the importance of older consumers, with the over 55s now expected to make up two thirds of all retail activity by 2025.</p> <h3>Advertisers wasted over 600m on non-viewable ads in 2016</h3> <p>According to the latest report from Meetrics, UK advertisers spent approximately £606m on online ads that failed to meet the minimum viewability standards in 2016.</p> <p>In the final quarter of the year, just 49% of banner ads met the recommendation that 50% of the ad is in view for at least one second.</p> <p>Despite the figure being a slight improvement on Q2, it still remains a noticeable drop from the 54% viewability level of Q1 2016.</p> <p>In comparison to other European countries, this means the UK is lagging behind, with Austria and France having 69% and 60% viewability levels respectively. </p> <p><img src="https://assets.econsultancy.com/images/0008/3229/Viewability.png" alt="" width="540" height="371"></p> <h3>50% of consumers uninspired by finance marketing</h3> <p>A new study by 3radical has delved into consumer perceptions of marketing campaigns across the UK’s largest industries.</p> <p>Efforts from banks and brands within the finance industry were found to be the most ineffective, with 50% of survey respondents citing marketing campaigns as uninspiring. </p> <p>38% of consumers said the same thing about fashion and beauty marketing, making it the second-worst performing industry. In contrast, supermarkets and technology brands both scored well, with 80% of Brits believing supermarkets’ marketing to be effective, and 79% saying the same for technology brands.</p> <h3>Email rated as the best performing marketing channel</h3> <p>According to the DMA’s latest benchmarking report, email remains in good health, with 41% of marketers rating it as the best-performing channel.</p> <p>Now at 98%, email delivery rate is at its highest ever, increasing by 11 percentage points since 2010. </p> <p>Lastly, despite some decline in recent years, unique open rates and unique click-to-open rates remain steady, currently at 15% and 20% respectively.</p> <p><em>Total emails delivered</em></p> <p><img src="https://assets.econsultancy.com/images/0008/3227/DMA_email.JPG" alt="" width="622" height="404"></p> <h3>Aldi named as one of the UK’s most customer-centric retailers</h3> <p>Dunnhumby’s latest global index report has revealed that Aldi, Lidl and Tesco are the UK’s most customer-centric retailers.</p> <p>The findings are based on the key drivers behind a customer’s likelihood to repurchase from a retailer as well as desire to recommend it, including factors like ‘affinity’, ‘range and service’ and ‘rewards’.</p> <p>Aldi was ranked highest for ease and price, Tesco for its customer loyalty programmes, and Lidl for its value-focused approach.</p> tag:econsultancy.com,2008:BlogPost/68708 2017-01-19T02:00:00+00:00 2017-01-19T02:00:00+00:00 Three key marketing skills for 2017 Jeff Rajeck <p>Naturally, <strong>marketers want to focus on what will give them the most 'bang for their buck'</strong>, though. They need to know what technologies have improved recently or what techniques are producing great results elsewhere.</p> <p>In order to find out what these key skills are right now, we recently asked a number of industry experts to comment on<strong> what they see as the most important marketing technologies and techniques for the coming year</strong>.  </p> <p>Below is the answer from Janet Low, Vice President of Client Services in APAC at Epsilon International, followed by some comments on each of the skills she regards as key in 2017.</p> <p><iframe src="https://www.youtube.com/embed/5yCH5BFkN74?wmode=transparent" width="560" height="315"></iframe></p> <h3>1. CRM</h3> <p>The customer relationship management (CRM) system has been a part of marketing technology for many years.</p> <p>What Ms Low points out, though, is that<strong> the CRM can now provide business value across the whole customer lifecycle</strong>. This means that marketers should become more familiar with the CRM now as it is more than the system used only by the call centre.</p> <p>Marketers from a <a href="https://econsultancy.com/blog/67978-three-ways-digital-marketers-in-mumbai-increase-customer-engagement/">recent roundtable event in Mumba</a>i agreed with this notion. Attendees pointed out that CRM data can be used for:</p> <ul> <li>Improving targeting with email marketing.</li> <li>Building audiences with Facebook and Google.</li> <li>Segmenting customers using attributes such as purchase history and website behaviour, and not just age and gender.</li> </ul> <p><img src="https://assets.econsultancy.com/images/resized/0007/6279/india-indulge-blog-flyer.jpg" alt="" width="470" height="353"></p> <p>For those who have not yet tapped into the 'CRM goldmine', 2017 is a great time to start.</p> <h3>2. Applied analytics</h3> <p>Analytics have been a key component of a marketer's toolbox for at least a century, but their usefulness was limited due to the lack of high-quality data. Marketers now have sufficient data to be confident about conclusions drawn from analysis and so applied analytics is now becoming a greater part of their job.   </p> <p>Participants at an <a href="https://econsultancy.com/blog/67922-really-big-data-managing-customer-insights-in-china/">Econsultancy event in Shanghai</a> last year, came up with<strong> three ways in which they make decisions using analytics</strong>: </p> <ol> <li> <strong>Delivering customized content</strong> using data from customer profiles.</li> <li> <strong>Changing the frequency of messaging</strong> according to the success rates of email and ad campaigns.</li> <li> <strong>Updating brand creative</strong> based on the feedback they get from social media and customer reviews regarding how well consumers understand the brand.</li> </ol> <p> So, 2017 is the year for analytics to break out of the back room and become part of the front-line strategy.</p> <p><img src="https://assets.econsultancy.com/images/0007/5696/4__Custom_.jpg" alt="" width="800" height="533"></p> <h3>3. Customer journey mapping</h3> <p>Analytics can also help marketers understand their customers better. Previously, a lot of assumptions had to be made about the customer journey, but now there is data showing which touchpoints consumers have hit along the way to becoming customers. </p> <p>In a <a href="https://econsultancy.com/reports/customer-experience-maturity-in-australia-and-new-zealand/">recent survey</a>, however, marketers in Australia and New Zealand indicated that <strong>only half (50%) of companies in the region had at least an 'intermediate' understanding of the customer journey</strong> and only around a third had any budget allocated for improving the situation.</p> <p><img src="https://assets.econsultancy.com/images/0007/4671/3.PNG" alt="" width="499" height="331"></p> <p>What this means is that<strong> marketers who take up the mantle and spend time on the customer journey are likely to benefit by pulling ahead of the competition</strong>.  Some benefits include more efficient media spend, improved customer metrics such as Net Promoter Score, decreased time-to-conversion, and greater customer retention.</p> <p>With so many good reasons to map the customer journey, it's surprising that more companies haven't done it already. And, as Econsultancy's Ben Davis says, mapping the customer journey <a href="https://econsultancy.com/blog/68681-mapping-the-customer-journey-doesn-t-have-to-be-difficult/">doesn't have to be difficult</a>.</p> <p>So while it still will not be possible for marketers to relearn everything in 2017, there are some key activities which industry experts and other marketers globally will be prioritising this year. To keep up, marketers need to reflect on these topics and ensure that their skills are up-to-date. </p> <p><em>To improve your own digital skills in 2017, check out our <a href="https://econsultancy.com/training/">global range of training courses</a>. </em></p> <p><em>Or to benchmark your knowledge against industry peers, complete our <a href="https://econsultancy.com/training/digital-skills-index-lite/">Digital Skills Index</a>.</em></p> tag:econsultancy.com,2008:BlogPost/68713 2017-01-18T14:06:44+00:00 2017-01-18T14:06:44+00:00 62% of businesses have no data analytics strategy: report David Moth <p>With this in mind I took a look at our recent <a href="https://econsultancy.com/reports/measurement-and-analytics-report/">Measurement and Analytics Report 2016</a>, published in association with Lynchpin, to gain some insight on how we stack up against other businesses.</p> <p>The report, which is based on a survey of almost 1,000 digital professionals, shows that 42% of businesses don’t have a framework for structuring their measurement requirements.</p> <p>Structuring data and processes is essential when it comes to building an overall view of the current analytics capabilities within your organisation which, in turn, allows progress and improvement based on testing and learning.</p> <p>Perhaps unsurprisingly, the likelihood of an organisation having a measurement framework increases with turnover. Companies with an annual turnover of more than £50m are 58% more likely to have a framework in place.</p> <p>The size of the team designated to handle data also has a profound impact, with a larger team (five or more) increasing the likelihood of having a framework by 35%.</p> <p><img src="https://assets.econsultancy.com/images/0008/3134/measurement_frameworks_by_turnover.png" alt="" width="700" height="145"></p> <p>Econsultancy remains a small business, so I’m pleased that we are among the minority of SMEs with a measurement framework in place.</p> <h3>Data strategy</h3> <p>The research also asked respondents about the strategy that underpins their measurement and analytics.</p> <p>Almost two-thirds (62%) of companies do not have a formally documented data analytics strategy, which is only a 6% decrease on the 2015 survey.</p> <p>The fact that more organisations do not have a formal strategy implies this is an area where there is room for improvement in terms of a framework. Without a strategy in place, it is difficult to take clear measurements and consistently track whether or not KPIs are being met.</p> <p>Furthermore, around a fifth (19%) of companies who do have a formal data analytics strategy report that it is for digital analytics only.</p> <p>Having a merged strategy incorporating both offline and online channels should be the goal for most companies, particularly as almost two-thirds (64%) of client-side respondents said they don’t have a marketing attribution model.</p> <p><em>For more on this topic, download the full <a href="https://econsultancy.com/reports/measurement-and-analytics-report/">Measurement and Analytics Report</a>.</em></p> tag:econsultancy.com,2008:BlogPost/68638 2017-01-04T14:32:41+00:00 2017-01-04T14:32:41+00:00 Predictive analytics: What are the challenges and opportunities? Arliss Coates <p><strong>From automation to automaton?</strong></p> <p>Time was identified as a business's most precious resource. Being able to streamline the marketing function through automation and, in particular, the analytics portion, was something executives deemed hugely valuable.</p> <p>But is automation driving out innovation and originality? With so much potentially determined by machines and algorithms, do brands risk losing the essence that made them unique and the innovation that could keep them alive?</p> <p><strong>Understanding where automation delivers real results</strong></p> <p>Nearly 60% of respondents stated that their analytics solutions produced data-based insights without analyst involvement.</p> <p>A further 80% of those stated it saved them significant time as a result. Either the analysts themselves could be redeployed to focus on trickier tasks or the insights generated pointed to opportunities elsewhere.</p> <p>Hotel group IHG's head of CRM, Jim Sprigg, explains his position on automation thusly: "Automation and machine learning will be critical for the sort of thinking that requires many calculations done in a somewhat predictable way."</p> <p>"It is definitely in our roadmap for broad use in predictive modeling which can drive, say, the assignment of offers and content in digital media based on individual customers' attributes, behaviors and transaction histories."</p> <p><strong>Dealing with the routine but complex</strong></p> <p>The idea of automation means different things to different people. For some organizations, particularly those that operate well on defined processes and rules-driven decision making, automation saves a great deal of time.</p> <p>This is either because it can create a trickle down effect of automation allowing other systems to take appropriate action without human intervention, or alert business users when intervention is needed.</p> <p>In complex, real time environments such as programmatic advertising, the automated processing of information into insights, and insights into action is viewed as essential to realizing opportunities before they pass brands by.</p> <p>Danish AI-based media buying agency, Blackwood Seven, is expanding across Europe based on the success of its model that claims clients get a 25-50% improvement in the effect of their media (<a href="http://www.campaignlive.co.uk/article/blackwood-sevens-ai-media-agency-provoking-fear-across-big-networks/1411733">according to <em>Campaign </em>magazine</a>) through using the company's AI technology.</p> <p><iframe src="https://player.vimeo.com/video/170621249?title=0&amp;byline=0&amp;portrait=0" width="640" height="360"></iframe></p> <p>The software analyzes 82 different data inputs (such as sales, YouGov data and weather info) to determine a media plan's likely outcome and optimizes in real time accordingly.</p> <p><strong>Can we automate creativity?</strong></p> <p>The advertising community is already looking at the question of whether or not automation and machine learning can actually create ad executions, not just supply humans with the insight with which to build their own creations.</p> <p>However, the idea that AI would be integral to developing creative is still a pipedream. This begs the question, beyond a degree of grunt work or speedy number crunching to get the the right ads to the right audiences in real time, does automation have anything to contribute to the creative, innovative side of marketing.</p> <p>In a discipline that has always been described as the marriage of art and science, can science begin to replicate (and replace) art?</p> <p><strong>The limits of automation</strong></p> <p>There is a sense, however, that analytics will never fully be automated. The feeling persists that strong marketing is an intelligent marriage of art and science, even in today's data obsessed environment.</p> <p>"Humans still have an advantage over computers," Sprigg insists. "We used to call these the big 'ah-ha' insights. The sort that come from intuition and highly synthesized recognition."</p> <p>Sprigg gives the example of a time he showed the output from an automated learning process that suggested some offers landed differently with customers who came to the company via customer service than for those who used the web.</p> <p>The group to whom Sprigg presented this data made the connection between the streams of information the computers already had access to - that there was a gap in the merchandising. "Humans were synthesizing information along with practical human experience in ways that we would have never known to code into the computer's consideration set," he adds.</p> <p>Sprigg identifies that the biggest problem with automated analytics may yet be human in origin - it is a case of scenario planning.</p> <p>Programmed with the information around any given scenario, a computer could undoubtedly come up with the relevant insight. It's just that humans cannot prepare the machines to anticipate every possible nuance or scenario.</p> <p>"Marketing functions can't build automation for out-of-the-box thinking, but they can recruit for it," Sprigg concludes.</p> <p>Humans, while lacking in the number crunching abilities of their automated colleagues, benefit from years of emphatic "programming" that contributes hugely to strategic success.</p> <p><strong>The dangers of machine-based innovation</strong></p> <p>While marketers may be in danger of forgetting the worth of their human resources in favor of the speed and efficiency of automation, there is also a danger in relying 100% on data outputs to inform future direction.</p> <p>Some executives interviewed for this report warned that an over-reliance on data to substantiate decision-making was hampering innovation.</p> <p>The Hard Rock Cafe's Claudia Infante complains that "the ideas that get shelved are the victims of a hybrid data-driven culture that we're creating around ourselves."</p> <p>"We're no longer as nimble and willing to go looking for the new shiny thing because we have to look at the data. There is no data to back those ideas up and you can't get data unless you activate the idea."</p> <p><img src="https://assets.econsultancy.com/images/0008/2793/magpie.jpg" alt="" width="413" height="316"></p> <p><strong>Paralysis by analysis</strong></p> <p>Automation builds a data-driven culture because it allows for faster reporting, analysis and optimization of existing channels, building on what is known. This use of data as a comfort blanket, however, can slowly suffocate innovative organizations.</p> <p>On that note, Infante adds that "a company may have been innovative and forward thinking but of course it grows on the back of that success. Then, when you're a big player, you have to take care of the day-to-day: make sure the lights are on, guarantee growth. As a result, we end up leaving behind a bit of that ideation process."</p> <p>It's clear from Infante's illustration that companies need to make sure they continue to use automation as a solution to an existing problem rather than a panacea for everything.</p> <p>It may seem faster, and the results from it more tangible, but automation is not going to deliver on every aspect. It's all about finding its place.</p> <p>"Companies have many people analyzing reports trying to identify tactical performace gaps and opportunities so they make predictable adjustments. As a result, companies hire a lot of people who like trying to think like a computer. If that can all be automated, the goal should be to recruit different types of thinkers," Sprigg explains. </p> <p><strong>Automation must be omni-channel</strong></p> <p>The immediate challenge for developers of analytics automation is in creating a solution that moves beyond the point and into an omni-channel environment. IHG's Sprigg explains:</p> <p>"Out-of-the-box solutions tend to be limited in their scope of operations. They are designed to optimize one channel or only one page at a time. This is multichannel optimization. We want to optimize in a way that allows us to maintain a consistent omni-channel experience across all channels and even extends to customer service and in-hotel interactions."</p> <p><strong>Understand the question before anticipating the answer</strong></p> <p>Over and over again however, executives have reinforced the old computing adage of "garbage in, garbage out." Automation in analytics is only ever going to be as good as the premise it is set up to work toward. Marketers must understand its power and its limitations to fully benefit from its potential.</p> <p>For some, it is a simple question of plug and play to speed up number crunching and use the efficiencies to divert resources elsewhere.</p> <p>Other organizations may find that embedding automation in their analytics process requires a wholesale change of departmental and HR organization. In some cases the whole culture of the company could change.</p> <p><em>This post was co-written by Morag Cuddeford-Jones.</em></p> tag:econsultancy.com,2008:Report/1980 2017-01-01T00:00:00+00:00 2017-01-01T00:00:00+00:00 Digital Intelligence Briefings Econsultancy <h3>Download the latest Digital Intelligence Briefing (2017 Digital Trends) <a title="Digital Intelligence Briefing: 2017 Digital Trends" href="https://econsultancy.com/reports/digital-intelligence-briefing-2017-digital-trends/">here</a>.</h3> <p>Econsultancy's <strong>Digital Intelligence Briefings </strong>look at some of the most important trends affecting the marketing landscape.</p> <p>Marketers around the world are surveyed on a regular basis to give an accurate bellwether of trends that matter to marketers. Each year kicks off with a broader view on where marketers are focusing their attention. For the rest of the year, Econsultancy’s Research Team dig into some of the key trends to add depth and insight.</p> <p>These reports will benefit senior marketers with budget and planning responsibility who wish to benchmark themselves against their industry peers. They provide many stats and data points to assist with business cases, presentations and client pitches.</p> <p>The Digital Intelligence Briefings are sponsored by <a title="Adobe" href="http://www.adobe.com/solutions/digital-marketing.html">Adobe</a>.</p> <p><strong>2017</strong></p> <ul> <li><a title="Digital Intelligence Briefing: 2017 Digital Trends" href="https://econsultancy.com/reports/digital-intelligence-briefing-2017-digital-trends/">2017 Digital Trends</a></li> </ul> <p><strong>2016</strong></p> <ul> <li><a title="Quarterly Digital Intelligence Briefing: 2016 Digital Trends" href="https://econsultancy.com/reports/quarterly-digital-intelligence-briefing-2016-digital-trends/">2016 Digital Trends</a></li> <li><a title="Quarterly Digital Intelligence Briefing: The Pursuit of Data-Driven Maturity" href="https://www.econsultancy.com/reports/quarterly-digital-intelligence-briefing-the-pursuit-of-data-driven-maturity/">The Pursuit of Data-Driven Maturity</a></li> <li><a title="Digital Intelligence Briefing: Taking Advantage of the Mobile Opportunity" href="https://econsultancy.com/reports/digital-intelligence-briefing-taking-advantage-of-the-mobile-opportunity/">Taking Advantage of the Mobile Opportunity</a></li> <li><a title="Digital Intelligence Briefing: Succeeding in the Omnichannel Age" href="https://econsultancy.com/reports/digital-intelligence-briefing-succeeding-in-the-omnichannel-age/">Succeeding in the Omnichannel Age</a></li> </ul> <p><strong>2015</strong></p> <ul> <li><a href="https://econsultancy.com/reports/quarterly-digital-intelligence-briefing-2015-digital-trends/">2015 Digital Trends</a></li> <li><a title="Quarterly Digital Intelligence Briefing: The Quest for Mobile Excellence" href="https://econsultancy.com/reports/quarterly-digital-intelligence-briefing-the-quest-for-mobile-excellence">The Quest for Mobile Excellence</a></li> <li><a title="Quarterly Digital Intelligence Briefing: The Multichannel Reality" href="https://econsultancy.com/reports/the-multichannel-reality/">The Multichannel Reality</a></li> <li><a href="https://econsultancy.com/reports/quarterly-digital-intelligence-briefing-the-cx-challenge/">The CX Challenge</a></li> </ul> <p><strong>2014</strong></p> <ul> <li><a title="Quarterly Digital Intelligence Briefing: 2014 Digital Trends" href="http://econsultancy.com/reports/quarterly-digital-intelligence-briefing-2014-digital-trends">Digital Trends for 2014</a></li> <li><a title="Quarterly Digital Intelligence Briefing: Finding the Path to Mobile Maturity" href="https://econsultancy.com/reports/quarterly-digital-intelligence-briefing-finding-the-path-to-mobile-maturity">Finding the Path to Mobile Maturity</a></li> <li><a title="Quarterly Digital Intelligence Briefing: Delivering Digital Experiences" href="https://econsultancy.com/reports/quarterly-digital-intelligence-briefing-delivering-digital-experiences">Delivering Digital Experiences</a></li> <li><a href="https://econsultancy.com/reports/quarterly-digital-intelligence-briefing-why-marketing-should-be-personal/">Why Marketing Should Be Personal</a></li> </ul> <p><strong>2013</strong></p> <ul> <li> <a title="Quarterly Digital Intelligence Briefing: Digital Trends for 2013" href="http://econsultancy.com/reports/quarterly-digital-intelligence-briefing-digital-trends-for-2013">Digital Trends for 2013</a> </li> <li> <a title="Quarterly Digital Intelligence Briefing: From Content Management to Customer Experience Management" href="http://econsultancy.com/reports/quarterly-digital-intelligence-briefing-from-content-management-to-customer-experience-management">From Content Management to Customer Experience Management</a> </li> <li><a title="Quarterly Digital Intelligence Briefing: Optimising Paid Media" href="http://econsultancy.com/reports/quarterly-digital-intelligence-briefing-optimising-paid-media">Optimising Paid Media</a></li> <li><a title="Channels in Concert: Trends in Integrated Marketing" href="http://econsultancy.com/reports/quarterly-digital-intelligence-briefing-integrated-marketing">Trends in Integrated Marketing</a></li> </ul> <p><strong>2012</strong></p> <ul> <li><a title="Digital Trends for 2012" href="http://econsultancy.com/reports/quarterly-digital-intelligence-briefing-digital-trends-for-2012/">Digital Trends for 2012</a></li> <li><a title="Quarterly Digital Intelligence Briefing: Personalisation, Trust and Return on Investment" href="http://econsultancy.com/reports/quarterly-digital-intelligence-briefing-personalisation-trust-and-roi">Personalisation, Trust and Return on Investment</a></li> <li><a href="http://econsultancy.com/reports/quarterly-digital-intelligence-briefing-managing-and-measuring-social">Managing and Measuring Social</a></li> <li><a title="Quarterly Digital Intelligence Briefing: Making Sense of Marketing Attribution" href="http://econsultancy.com/reports/quarterly-digital-intelligence-briefing-making-sense-of-marketing-attribution">Making Sense of Marketing Attribution</a></li> </ul> <p><strong>2011</strong></p> <ul> <li><a title="Digital Trends for 2011" href="http://econsultancy.com/reports/quarterly-digital-intelligence-briefing-q2-2011">Digital Trends for 2011</a></li> <li><a href="http://econsultancy.com/reports/quarterly-digital-intelligence-briefing-q3-2011">Impact of Marketing Technology on Business</a></li> <li><a title="Quarterly Digital Intelligence Briefing: Social Data" href="http://econsultancy.com/reports/quarterly-digital-intelligence-briefing-social-data">Social Data</a></li> </ul> <p><em>All reports are free to download as part of an Econsultancy subscription.</em></p> <h3><strong>More trends analysis from Econsultancy</strong></h3> <p>Enterprise subscribers also have access to <a title="Econsultancy Digital Shift" href="https://econsultancy.com/reports/digital-shift">Digital Shift</a>, a quarterly service which curates and interprets the most important developments, trends and innovation. Our aim? To make it simple for you to keep track of the key developments in digital technology and marketing. </p> <h4>Find out more about Econsultancy subscriptions</h4> <p>Email us on <a href="mailto:subscriptions@econsultancy.com">subscriptions@econsultancy.com</a>.</p> <p>Or call your local team:</p> <ul> <li>EMEA: Paul Simmons, +44 (0)20 3199 7118</li> <li>Americas: Alex Nodell, +1 212 971 0631</li> <li>APAC: Jefrey Gomez, +65 6653 1911</li> </ul> tag:econsultancy.com,2008:BlogPost/68661 2016-12-23T00:01:00+00:00 2016-12-23T00:01:00+00:00 Five trends which will define data-driven marketing in 2017 Jeff Rajeck <p>Speaking to company marketers at a recent Digital Cream Singapore, though, it seems that others have a much different view of marketing data.</p> <p>Many attendees indicated that they are no longer just handing over their data to demonstrate return on investment (ROI), but they are instead using it to change the way their marketing team works.</p> <p>Below are five trends which roundtable participants felt will define data-driven marketing in the coming year.</p> <h3>1) Marketers will increasingly use data for decision making</h3> <p>One trend that most participants agreed on is that that data will be used more often to drive marketing decisions in 2017. Attendees said that data analysis was the best way to find the 'low-hanging fruit' which improves marketing performance.</p> <p><a href="https://econsultancy.com/reports/measurement-and-analytics-report">A 2016 Econsultancy survey</a> of client-side marketers backs up this notion. In the study, marketers were asked to indicate what percentage of their data was useful for decision making and less than one in three (29%) indicated that very little (0-25%) of their data was useful.</p> <p>In the same survey, marketers also agreed overwhelmingly (84%) that analytics drives actionable recommendations which make a difference to their organisation.</p> <p><img src="https://assets.econsultancy.com/images/0008/2614/figure1.png" alt="" width="800" height="367"></p> <p>While optimistic in general, participants also felt that using data to help make marketing decisions also raises new issues.</p> <p>First off, many said that marketers are suffering from data overload. Each channel, every customer touchpoint, and each marketing system has its own data and participants felt that all the data was becoming overwhelming.</p> <p>One delegate mentioned that their customers use chat apps when purchasing and the marketing team found it difficult to use this data for attribution.</p> <p>Another problem with using data for decision making is that additional resources are required to make sense of the data. Companies with small or stretched marketing teams struggle to find the time to analyse the data to an extent where it offers useful insights.</p> <p>Also, while using data can make some decisions easier, data-based decisions can become politicized, too (see point 3 below).</p> <p><img src="https://assets.econsultancy.com/images/0008/2619/2__Custom_.jpg" alt="" width="800" height="533"></p> <h3>2) Agile marketing will become more popular</h3> <p>Interestingly, attendees said that the increased use of data in marketing will allow marketers to work in a more agile manner.</p> <p>Described in a <a href="https://econsultancy.com/blog/68373-what-is-agile-marketing-and-what-do-marketers-think-about-it/">previous article</a>, 'agile marketing' is essentially a working method which encourages individual efforts and frequent collaboration.</p> <p><img src="https://assets.econsultancy.com/images/0007/9892/agile-wall-3.jpg" alt="" width="800" height="600"></p> <p>According to participants agile marketing is enabled by data because group decisions are guided by facts rather than 'the HIPPO' (Highest Paid Person's Opinion). As a result, marketers feel empowered to share details about their work and meetings become more productive. </p> <p>Those aiming to implement agile marketing will still face challenges, though. Companies with a conservative culture may find it hard to accept its unorthodox working methods.</p> <p>Additionally, for agile to work, marketers must be willing to put in extra hours to learn about how to run tests correctly and explain results in detail.</p> <p>Attendees who had already implemented agile marketing said that the results were encouraging. One reported that projects which used to take two to three months, now only took two to three weeks.</p> <p><img src="https://assets.econsultancy.com/images/0008/2620/4__Custom_.jpg" alt="" width="800" height="533"></p> <h3>3) Marketing attribution will still be difficult</h3> <p>While all attendees agreed that they would like to attribute conversions across channels, many feel that they are still some ways away from being able to do so.</p> <p>The first problem attendees highlighted was that the marketing attribution has become political at some organisations. This happens because channel budgets are often set according to how much revenue a channel provides. Channel managers, therefore, are motivated to 'talk up' the value of their channel even if the data does not support it.</p> <p>Another problem was the number of channels. Delegates reported that some of their customers hit 10 or more touchpoints before converting. Piecing together a customer journey of that length and attributing value to each step is a difficult, if not impossible, task.</p> <p>Finally, marketers said that even if the journey could be mapped and an attribution model agreed upon, not all of the data is available. New digital channels are popping up all of the time and many do not integrate with analytics systems (see <a href="https://econsultancy.com/blog/68223-dark-social-it-s-worse-than-we-thought-in-asia-pacific/">Dark social: It's worse than we thought in Asia-Pacific</a>). To add to the problem, offline data is typically even more difficult to obtain than online.</p> <p>So, while marketing attribution will remain a goal of many companies, participants predicted that few will make as much progress toward marketing attribution in 2017 as they would like.</p> <p><strong><img src="https://assets.econsultancy.com/images/0008/2618/1.jpg" alt="" width="800" height="600"></strong></p> <h3>4) Marketers will personalise using data-driven customer insights</h3> <p>Personalisation is already in use at many organisations, but often this meant using segments to deliver content which resonates more with the target audience.</p> <p>In the coming year, attendees felt that personalisation initiatives will be expanded so that consumers will be delivered the 'next best piece of content' to help them make buying decisions.</p> <p>In order to do so, marketers must be able to use the 'data exhaust' of consumer behaviour and use that as a way to determine which content to deliver via email, web, and mobile.</p> <p>Some participants felt that there were issues with this approach to personalisation. Many organisations still suffer from 'data silos' where one department would not allow another to use its data.  This is particularly true between sales and marketing.</p> <p>Others said that their marketing technology stack was not yet up to the task to handle individual personalisation. According to a recent Econsultancy survey, this seems to be the case at many organisations as only 7% strongly agreed that their current data architecture is an 'enabler for personalisation'.</p> <p><img src="https://assets.econsultancy.com/images/0008/2615/figure_20.png" alt="" width="800" height="478"></p> <h3>5) Media agencies will be held accountable for online advertising</h3> <p>Finally, attendees said that in 2017, client-side marketers will require that their agency partners provide more data about their online advertising.</p> <p>In the past, it seems that many marketing teams did not have the analytics capabilities to manage detailed data about ad performance. As a result, many agency reports contained only high-level figures.</p> <p>Now that client-side teams are becoming more data-driven, their expectations for both the quantity and the quality of the data will increase. Issues such as <a href="https://econsultancy.com/blog/67531-fake-likes-clicks-followers-in-asia-what-you-can-do-about-them/">click fraud</a>, <a href="https://econsultancy.com/blog/67366-three-display-advertising-issues-to-watch-in-2016/">viewability</a>, and <a href="https://econsultancy.com/blog/67334-disproving-the-myth-about-display-clicks-conversions/">view-through conversions</a> will become frequent topics of conversations between agencies and data-driven marketing teams.</p> <p>There are still hurdles though. First off, advertising data is complicated and it will take some time for agencies and marketing teams to 'get on the same page', according to one participant.</p> <p>Also, as mentioned above (point 3), even when ad data is understood it still may not help marketers allocate media spend by the effectiveness of the channel.</p> <p>Finally, agencies suffer from the same issue that marketing teams do - they simply do not have all the data. Many online conversions and purchases come through channel partners, such as marketplaces, which do not provide attribution data to their members.</p> <p>So, even with all of the view and click data at hand, marketers who use channel partners will still struggle to know which advertising platforms provide the most value to the business.</p> <h3>A word of thanks</h3> <p>Econsultancy would like to thank all of the marketers who participated at Digital Cream Singapore 2016 and our table moderator for Data-Driven Marketing &amp; Marketing Attribution Management - Frederick Tay, Associate Director, Marketing Operations, INSEAD.</p> <p>We hope to see you all at future Singapore Econsultancy events!</p> <p><img src="https://assets.econsultancy.com/images/0008/2621/end__Custom_.jpg" alt="" width="800" height="533"></p> tag:econsultancy.com,2008:BlogPost/68616 2016-12-22T14:21:00+00:00 2016-12-22T14:21:00+00:00 Learning to trust the machines: AI and company culture Ben Davis <h3>The rise of the machines</h3> <p>Machine learning is used to predict how people will react, which is basically what all marketers want to understand.</p> <p>Applications include:</p> <ul> <li>personalising advertising</li> <li>informing stock levels</li> <li>providing customer service (fairly nascent)</li> <li>conversion optimisation (copy and web design)</li> <li>recommendations</li> <li>lead generation (from unstructured text analysis) </li> <li>image recognition</li> <li>search (natural language processing)</li> <li>fraud detection</li> <li>sentiment analysis </li> </ul> <p>Though in some areas such as search and advertising, machine learning has been working in the background for a while and is an implicit part of their functionality, in other areas the rise of machines presents a cultural issue.</p> <p>In lead generation, for example, it's understandable that those with 30 years experience of an industry are sceptical when told that an algorithm will be better at finding the right accounts to target.</p> <p>I recently spoke with Aman Naimat, SVP Technology at Demandbase, the company that has developed <a href="https://www.demandbase.com/demandgraph/">Demandgraph</a>, an AI solution for account targeting. As impressive as the technology is, Aman confirmed that cultural issues are probably the most pressing challenge when it comes to adoption (over integration, for example).</p> <h3>What do we know about human-machine trust?</h3> <p>The notion of human-machine trust has probably never been as pertinent as it is today, with semi-autonomous cars already on the market and self-driving cars well on the way to realisation.</p> <p>Would you want a self-driving car to sacrifice you, the pilot, in order to save the lives of multiple pedestrians when an accident is inevitable? Most people agree on <a href="https://www.technologyreview.com/s/542626/why-self-driving-cars-must-be-programmed-to-kill/">the ethical answer to this question</a> (self-sacrifice), but wouldn't want to drive such a car.</p> <p>Of course, if people refused to buy such autonomous cars, more traffic deaths would occur; a Catch-22 situation.</p> <p>Away from such gory matters, how do people feel about machines helping them take decisions in nuanced, work-based scenarios? </p> <p>At the Singapore University of Technology and Design, Jessie Yang and Katja Hölttä-Otto designed an experiment. Human participants took part in a memory and recognition task using an automated decision aid.</p> <p>The task involved the memorising of images, which were later to be selected from a pool of similar images. The automated decision aid provided recommendations but, crucially, was designed to do so reliably for some participants and not so reliably for others.</p> <p><a href="http://news.mit.edu/2016/building-better-trust-between-humans-and-machines-0621">As detailed by MIT News</a>, the results revealed that the unreliable automated aids were overtrusted. Conversely, the highly reliable automated aids were undertrusted.</p> <p>On reflection, this seems somewhat like human nature. We may be keen to take advantage of AI but perhaps ultimately we don't fully trust it.</p> <p>Another experiment, this time at MIT by Yang and Julie Shah, Department of Aeronautics and Astronautics Assistant Professor, went one step further, looking at how interface design affects so-called 'trust-reliability calibration'.</p> <p>The pair were interested in alarm displays in high risk industries. Rather than the traditional “threat” or “no threat” alarm, often developed with very low thresholds (for obvious reasons), the introduction of likelihood alarm displays (how likely is the risk event?) could help to mitigate the "cry wolf" effect.</p> <p>Over time, these assessments of likelihood may ensure that trust in the warning system remains higher.</p> <p>Okay, this may seem like a far cry from marketing software, but the principles carry across industries. The more educated the end user, the better the relationship with intelligent technology.</p> <h3>Complexity = vulnerability </h3> <p><a href="http://www.britishscienceassociation.org/news/rise-of-artificial-intelligence-is-a-threat-to-humanity">Research by the British Science Association</a> revealed that 'half of those surveyed would not trust robots in roles including surgical procedures (53 per cent), driving public buses (49 per cent) or flying commercial aircraft (62 per cent).'</p> <p>It's arguably only education that can allay these fears.</p> <p>However, as Kalev Leetaru points out, <a href="http://www.forbes.com/sites/kalevleetaru/2016/01/04/in-machines-we-trust-algorithms-are-getting-too-complex-to-understand/#32c2d1fd2f14">writing for Forbes</a>, even with an increased understanding of how machine learning works, the complexity of web-based services can still scupper trust.</p> <p>Kalev describes systems 'built on top of a layer of trust of other systems such that an error, vulnerability, or mistaken understanding at any level can cascade across the system'. For example:</p> <ul> <li>in 2013 Microsoft’s Azure service faced a worldwide outage due to a simple expired SSL certificate</li> <li>in 2012 a leap day caused an outage when one Microsoft cloud system misunderstood what another was doing</li> <li>in 2013 when a single developer at Amazon was able to impact an entire data center at the height of the Christmas shopping season</li> <li>At the end of 2015, Google experienced an outage when connecting a new network link in Europe manually, which overrode automated safety checks</li> </ul> <p>With education, we can observe that however sophisticated machine learning becomes, it still relies on other infrastructure and data quality. Ultimately, it is still human-limited and we are still refining our trust-reliability calibration.</p> <p>This can be observed anecdotally. Look at the tweet below, something we're all familiar with. Retargeting and recommendations are incredibly powerful when implemented correctly, but the rules don't always stack up.</p> <blockquote class="twitter-tweet"> <p lang="en" dir="ltr">Amazon thinks my recent humidifier purchase was merely the inaugural move in a newfound hobby of humidifier collecting.</p> — Justin Shanes (@justinshanes) <a href="https://twitter.com/justinshanes/status/803453049603690496">November 29, 2016</a> </blockquote> <h3>So, how does this impact culture and strategy?</h3> <p>Enough of my secondary research into human-machine relationships. Aside from educating their employees, what do companies need to bear in mind when considering AI strategy?</p> <p>The main thing is data quality and scope. Supervised AI is only as good as its inputs, and all marketers should be aware of these inputs when relying on machine learning, just as they are when relying on statistical analysis. </p> <p>Richard Sargeant, director of ASI Data Science, a company that helps governments harness AI, <a href="https://www.publictechnology.net/articles/opinion/changing-culture-what-government-must-do-make-most-ai">has recently written</a> about the way that siloed departments can hinder the effectiveness of AI.</p> <p>Here's the important bit about data scope:</p> <blockquote> <p>Government is usually organised by service [(education, health etc)]. ..But this is not sensible in an AI age: if an agency is good at running one kind of digital service, chances are they’ll be good at running a bunch of them.</p> <p>...The most important factor in determining whether [a department] succeeded [in digital] wasn’t their knowledge of their departmental subject matter, but whether they had the organisational leadership and culture to develop and run digital services.</p> <p>And the departmental silos continue to make it very hard for datasets to work together.</p> <p>Why don’t we check benefit records against the death register to avoid paying benefits to people who are dead? Because they are run by separate departments.</p> <p>Why don’t we have one consistent list of companies in the UK? Because HMRC and Companies House maintain their own separate lists.</p> <p>The quality of machine learning and AI is heavily dependent on the quality and volume of data.</p> </blockquote> <p>Education, data quality and volume, transparency within the organisation - all are vitally important.</p> <h3>We still have a ways to go</h3> <p>Many of today's machine-learning powered solutions are 'human in the loop' solutions. That means they rely on humans to validate some of their findings and to provide feedback into the system.</p> <p>Humans in the loop can move AI from 80% accuracy to 90%+. And, of course, algorithms are limited by the humans that set them a-whirring, and the data they are using.</p> <p>That means the role of humans has not been diminished, rather it has increased in importance. We have to understand and govern this stuff.</p> <p><a href="https://www.facebook.com/notes/mark-zuckerberg/building-jarvis/10103347273888091/">In the words of Mark Zuckerberg</a>, 'we know how to show a computer many examples of something so it can recognize it accurately, but we still do not know how to take an idea from one domain and apply it to something completely different.'</p> <p>So, for the next decade at least, marketers and sales people should look upon AI as the incredibly powerful <em><strong>tool</strong></em> that it is.</p> <p><strong><em>Now read:</em></strong></p> <ul> <li><a href="https://econsultancy.com/blog/67745-15-examples-of-artificial-intelligence-in-marketing/">15 examples of AI in marketing</a></li> <li><a href="https://econsultancy.com/blog/68466-could-ai-kill-off-the-conversion-optimisation-consultant/%20">Could AI kill off the conversion optimisation consultant</a></li> <li><a href="https://econsultancy.com/blog/68388-how-klm-uses-bots-and-ai-in-human-social-customer-service/">How KLM uses bots and AI in 'human' social customer service</a></li> <li> <a href="https://econsultancy.com/reports/marketing-in-the-age-of-artificial-intelligence/">Marketing in the Age of Artificial Intelligence</a> </li> </ul>