Measurement of the customer experience with social media

  • Published on
    17-Jul-2015

  • View
    307

  • Download
    0

Embed Size (px)

Transcript

<ul><li><p>Monetising Social Media Engagement and the Measurement</p><p>Measuring the Value of the Customer Experience</p></li><li><p>FORWARD</p><p> Contained in this document is valid proof that social media brand conversations can be quantitatively measured and monetized. This represents a significant development and innovation in marketing measurement. It monetizes the customer experience and brings tangible and measureable value to the voice of the customer.</p></li><li><p>THE BEGINNING</p><p> A survey reveals that the best that social media data companies have to offer, customer sentiment metrics, fall significantly short in terms of fitting with or correlating to sales &amp; customer behavior</p><p> But a new metric comes along called the SEItm, which is based on deep rules of linguistics, language structure and language rules, that shows great promise</p><p> By testing different Sentiment Metrics, we discover that the new SEItm provides high statistical correlations and this leads us to expanded evaluation in different industry verticals. </p></li><li><p>AVAILABLE SOCIAL MEDIA SENTIMENT METRICS FALL SHORT AS A TOOLFOR MEASURING ROI, BUT THE SEITM SHOWS GREAT PROMISE</p><p>-20% 0% 20% 40% 60% 80% 100%</p><p>Sentiment Metric 1</p><p>Sentiment Metric 2</p><p>Sentiment Metric 3</p><p>Sentiment Metric 4</p><p>Sentiment Metric 5</p><p>Sentiment Metric 6</p><p>SOCIAL ENGAGEMENT INDEX POS/NEG RATIO</p><p>11.2%</p><p>3.1%</p><p>-2.3%</p><p>8.8%</p><p>21.2%</p><p>8.2%</p><p>83.1%</p><p>Figure 1: Compares correlation to sales of $6B client with SEI and sentiment metrics for 6 leading social data vendors, there is a wide gap.</p><p>Sentiment Metric 1</p><p>Sentiment Metric 2</p><p>Sentiment Metric 3</p><p>Sentiment Metric 4</p><p>Sentiment Metric 5</p><p>Sentiment Metric 6</p><p>SOCIAL ENGAGEMENT INDEXPOS/NEG RATIO</p></li><li><p>THE SOCIAL ENGAGEMENT INDEX OR SEITM, PROVIDES A UNIQUEAPPROACH FOR MEASURING THE CUSTOMER EXPERIENCE VIA SOCIAL</p><p>MEDIA</p><p> We specifically data mine for large quantities of social media brand conversations on Facebook, Twitter, Blogs, Boards, and specialized industry-specific review sites such as Yelp, Trip Advisor, etc. These conversations are typically reviews and playbacks about some aspect of a customers daily experience with a brand.</p><p> We divide these conversations into relevant topics or themes. For example, for an auto brand, that might be car acceleration, style, fuel economy, service issues, handling, reliability, etc.</p><p> We apply a linguistics methodology called stance shift. This is well published and reviewed academically. The basic premise here is that when there is a shift or pause in a posting or conversation, this is indicative that the customer is taking a position, opinion or is most engaged towards the particular subject inferred from the shift. By examining and scoring the emotional language and personalization expressed therein, we can get an accurate assessment of the level of engagement of that consumer towards the subject or brand in question.</p><p> We score the complete conversation or posting for emotional and personal language content. The methodology outlined here differs from many social media metrics because</p><p> We evaluate and score the entire conversation, and dont just use text analytics to extract key words or phrases</p><p> We build a custom dictionary with relevant and unique terms for each brand and industry We focus not just on content but also on context</p><p> With an average statistical correlation to sales of 77%, we are able to model and measure the customer experience and its importance in driving sales.</p></li><li><p>IN THE AUTO INDUSTRY, THE SEIsm IS STRONGLY CORRELATED TO NEWDEALER CAR SALES(72%)</p><p> - 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00</p><p>0</p><p>200</p><p>400</p><p>600</p><p>800</p><p>1,000</p><p>1,200</p><p>1,400</p><p>1,600</p><p>1,800</p><p> Actual SEI</p><p>SEI P</p><p>ositi</p><p>ve/N</p><p>egat</p><p>ive </p><p>Inde</p><p>x</p><p>6</p><p>DEALER CAR SALES</p></li><li><p>IN THE TELECOM INDUSTRY, THE SEIsm IS STRONGLY CORRELATED TONEW CUSTOMER ADDITIONS (85%)</p><p>0</p><p>100</p><p>200</p><p>300</p><p>400</p><p>500</p><p>600</p><p>70</p><p>90</p><p>110</p><p>130</p><p>150</p><p>170</p><p>190</p><p>210</p><p>230</p><p>250</p><p>6/16/2009 7/13/2010 8/9/2011</p><p>Cust</p><p>omer</p><p> Add</p><p>s In</p><p>dex</p><p>New Customer Sales Index SNI Ratio Index</p><p>SEI P</p><p>ositi</p><p>ve/N</p><p>egat</p><p>ive </p><p>Inde</p><p>x</p><p>7</p><p>TELECOM BRAND NEW CUSTOMER ADDITIONS</p></li><li><p>IN THE FOOD &amp; BEVERAGE INDUSTRY, THE SEIsm MIRRORSCOMPANY SEASONAL PATTERNS (84%)</p><p>8</p><p>TOTAL BEVERAGE BRAND SALES</p><p>SEIsm IS A REFLECTION OF TOTAL "WORD-OF-MOUTH" AND A PROXY FOR CONSUMER GOOD WILL</p><p>0</p><p>50</p><p>100</p><p>150</p><p>200</p><p>250</p><p> 80</p><p> 90</p><p> 100</p><p> 110</p><p> 120</p><p> 130</p><p> 140</p><p> 150</p><p> 160</p><p>07/08/08 08/04/09 08/31/10</p><p>Reta</p><p>il Sa</p><p>les I</p><p>ndex</p><p>TOTAL Retail.Sales SNI Positive/NegativeRatio</p><p>SEI P</p><p>ositi</p><p>ve/N</p><p>egat</p><p>ive </p><p>Inde</p><p>x</p></li><li><p>HOSPITALITY BRAND BOOKINGS</p><p> -</p><p> 20</p><p> 40</p><p> 60</p><p> 80</p><p> 100</p><p> 120</p><p> 140</p><p> 160</p><p> -</p><p> 20</p><p> 40</p><p> 60</p><p> 80</p><p> 100</p><p> 120</p><p> 140</p><p>1/6/2009 1/6/2010 1/6/2011</p><p>SEI </p><p>Posi</p><p>tive/</p><p>Neg</p><p>ativ</p><p>e In</p><p>dex</p><p>Book</p><p>ings</p><p> Inde</p><p>x</p><p>Bookings.Index SNI Positive/Negative Ratio</p><p>FOR A HOSPITALITY CLIENT, SEIsm IS A STRONG CORRELATE TO NEWBOOKINGS (77%)</p><p>THE METRIC USED WAS ONLINE REVIEW SITES FOR HOTELS, RESORTS AND CRUISE LINES. WEFOUND THE METRIC TO BE A PROXY FOR CUSTOMER SATISFACTION 9</p></li><li><p>THE CASE FOR SEIsm AS A PREDICTOR IS STRONGER AS IT HAS SHOWN TO BEA LEADING RATHER THAN A LAGGING INDICTOR FOR SALES</p><p> (0.20)</p><p> (0.10)</p><p> -</p><p> 0.10</p><p> 0.20</p><p> 0.30</p><p> 0.40</p><p> 0.50SEI Lead/Lag Correlations to Sales</p><p>Correlation</p></li><li><p>MONETIZING THE VALUE OF SOCIAL MEDIA THROUGHMARKETING-MIX MODELS</p><p> To fully leverage the SEI for our clients, the task is to understand its impact on their business.</p><p> By incorporating SEI metrics into marketing response (aka, mix) models, we can: Come to a better &amp; more precise understanding of how social media buzz </p><p>affects a clients business performance Understand the impact and interactions of the clients marketing and media as </p><p>it affects social media conversations about their brands. Provide strategic guidance as to the most effective ways for monitoring and </p><p>managing social media conversations on brands Our task is to build a nested model where SEI is both a dependent and a </p><p>predictor variable. In the former, SEI is a function of all media &amp; marketing efforts. In the latter, sales is a function of all media &amp; marketing plus the SEI. This approach not only enables us to understand the impact of Social Media </p><p>Word-of-Mouth, but also the influence of media and marketing on social media brand conversations.</p></li><li><p>A TWO-STAGE MODEL IS USED TO QUANTIFY THE DIRECT IMPACT OFMARKETING AND SOCIAL MEDIA ACTIVITIES ON SALES</p><p>1. Model the Social Engagement Index as a function of key marketing &amp; media drivers</p><p>2. Model retail time-sales as a function of media &amp; marketing drivers plus the SEI</p><p>56%</p><p>7%2%</p><p>5%</p><p>11%</p><p>19%</p><p>35%</p><p>Base Sales Conventional Marketing Campaigns Mkting campaigns on SM</p><p>Net Contribution of Marketing </p><p>2%+6% </p><p>+6% +13% = 27% Social Media Conversations</p><p>(SEI)</p><p>Sub-modelTotal Retail Sales Contribution</p><p>12</p><p>19%</p></li><li><p>A KEY INSIGHT DISCOVERED IS THAT NEGATIVE-SENTIMENTCONVERSATIONS HAD A SIGNIFICANTLY GREATER EFFECT THAN</p><p>POSITIVE ONES</p><p>ENSURE THAT YOUR BRAND IS REDUCING NEGATIVE TONED CONVERSATIONS</p><p>+4.4%</p><p>+16.5%</p><p>0%</p><p>5%</p><p>10%</p><p>15%</p><p>20%</p><p>Increase Positive Decrease Negative-30%</p><p>-20%</p><p>-10%</p><p>0%</p><p>10%</p><p>20%</p><p>30%</p><p>-100% -50% 0% 50% 100%</p><p>Sale</p><p>s Im</p><p>pact</p><p>Sale</p><p>s Im</p><p>pact</p><p>Change in "Engagement" by Tone</p><p>Total Retail Sales Sensitivity of Response(chg in Sales vs chg in Sentiment components of "Engagement")</p><p>Absolute Response (Based on Standard Favorable Move)</p><p>negative</p><p>positive</p><p>13</p><p>(Assumes 100% Decrease in Negative is not realistic)</p></li><li><p>WE CAN DETERMINE WHAT ELEMENTS OF THE CUSTOMER EXPERIENCE ISINCREASING AND DECREASING IN IMPORTANCE</p><p> -</p><p> 20.0</p><p> 40.0</p><p> 60.0</p><p> 80.0</p><p> 100.0</p><p> 120.0</p><p> 140.0</p><p> 160.0</p><p> 180.0</p><p>Last Year Current</p><p>low maintenancereliabilitya car to be seen drivingpower and accelerationstyleriding comfortcar handle and feel</p><p>Style, power and acceleration of the car is becoming more important in consumers minds</p></li><li><p>HOW SOCIAL MEDIA CHANNELS ARE DRIVING BRANDENGAGEMENT AND SALES</p><p>15</p><p>0.0</p><p>5.0</p><p>10.0</p><p>15.0</p><p>20.0</p><p>25.0</p><p>30.0</p><p>35.0</p><p>40.0</p><p>60</p><p>70</p><p>80</p><p>90</p><p>100</p><p>110</p><p>120</p><p>130</p><p>2009 2010 2011</p><p>Enga</p><p>gem</p><p>ent S</p><p>core</p><p>Sale</p><p>s Ind</p><p>ex</p><p>Sales &amp; Total Social Network Engagement Drivers by Channel</p><p>Facebook Twitter Boards Blogs &amp;Groups Sales Index</p></li><li><p>16</p><p>WHAT ARE THE STORIES OR CONTENT SHARED ABOUT YOUR BRANDTHAT IS MOST RELEVANT TO DRIVING REVENUE?</p><p>0.0</p><p>5.0</p><p>10.0</p><p>15.0</p><p>20.0</p><p>25.0</p><p>30.0</p><p>35.0</p><p>40.0</p><p>60</p><p>70</p><p>80</p><p>90</p><p>100</p><p>110</p><p>120</p><p>130</p><p>2009 2010 2011</p><p>Net</p><p>wor</p><p>k In</p><p>dex </p><p> Sco</p><p>re</p><p>Sale</p><p>s Ind</p><p>ex</p><p>Engaging Social Topics for a Restaurant Chain</p><p>Promotion A Place to Hang Out To Meet Friends and Associates Product B Product A Sales Index</p><p>The key topics/subjects of conversation about brands are scored. we can understand the reasons behind brand social media performance and can quantify these in terms &amp; monetize their value</p></li><li><p>0</p><p>5</p><p>10</p><p>15</p><p>20</p><p>25</p><p>30</p><p>35</p><p>Jun-</p><p>08</p><p>Sep-</p><p>08</p><p>Dec-</p><p>08</p><p>Mar</p><p>-09</p><p>Jun-</p><p>09</p><p>Sep-</p><p>09</p><p>Dec-</p><p>09</p><p>Mar</p><p>-10</p><p>Jun-</p><p>10</p><p>Sep-</p><p>10</p><p>Dec-</p><p>10</p><p>Mar</p><p>-11</p><p>Sponsorship EngagementNFL-FootballSponsorship EngagementPGA Golf</p><p>Super Bowl</p><p>Sponsored PGATournament</p><p>UNDERSTANDING THE KEY EVENTS AND FACTORS DRIVINGSPONSORSHIP AND BRAND ENGAGEMENT</p><p>SEI has been successfully used to measure and monetize the value of sports sponsorships</p></li><li><p>VALUING AND MONETIZING FACEBOOK MARKETING CAMPAIGNS</p><p> Because our Social Engagement Metric is part of a larger model, we can value events such as Facebook Campaigns. As shown below, the net consumer engagement is not necessarily the same as the volume of comments or the number of Likes.</p></li><li><p>Most Important Positive Drivers:</p><p>1. The Brand &amp; Place2. For Meeting People3. The Beverages4. The Store Atmosphere</p><p>Positive SEI 3.93 = 100</p><p>Place2HangOut &gt;5.46= 211</p><p>9.1%</p><p>Place2HangOut 9.43 = 325</p><p>2.6%</p><p>ToMeetPeople14.0 = 4660.6%</p><p>Beverage5.4 = 229 </p><p>3.8%</p><p>To Meet People6.4 = 271</p><p>7.7%</p><p>Beverage3.6 = 126</p><p>5.9%</p><p>Place2HangOut5.2 = 211.1 </p><p>1.6%</p><p>Atmosphere </p></li><li><p>THE BLUE-OCEAN OF SOCIAL MEDIA MEASUREMENT: KEY INSIGHTS</p><p> By linking a metric of Social Network Engagement to client sales, we have shown that this approach shows great promise as a diagnostic for understanding social medias impact on a clients business by including it as an input into marketing response (aka, mix) models. We have thus succeeded in measuring and monetizing the impact of social media on consumer demand.</p><p> We have also shown that these data provides deep insights about what moves brand performance in the market place, a new depth of understanding that could be considered a blue-ocean innovation.</p><p> Some of the key lessons that we have learned include: The impact of the SEI on brand performance tends to mirror the phenomena of word-of-mouth, which is a </p><p>known critical driver of most brands, but traditionally difficult to measure. Negative sentiment towards a brand have substantially greater impact on its performance than positive. It is </p><p>imperative that firms address expressed issues with these consumers and prevent the negative buzz from going widely viral.</p><p> For service based firms like the hospitality client, the social engagement from online reviews represents a measure of customer satisfaction, which is a dominant driver of these businesses. The social engagement metric here represents a promising tool for deriving customer service ratings for various business domains from such sites as Yelp, Expedia and Trip Advisor. </p><p> Our approach to Social Media Measurement provides a wealth of insights into why consumers buy your brand, how consumers engage with your brand and sponsorships and what particular social channels are most important in driving your brand. It monetizes the consumer experience.</p><p> That the direct impact of SEI on business is large and significant. A brands marketing and advertising has some effect on the SEI which in turn, affects sales.</p><p> We learned that the value and ROI of marketing is greatly enhanced due to the indirect effect it has on sales through its direct impact on Social Media Engagement (SEI )</p><p> That our SEI metric is no Holy Grail, but it shows much promise in delivering un-matched insights on how social media conversations have a direct and tangible impact on company performance.</p></li><li><p> Bottom-Line Analytics LLC is a consulting group focusing on a broad portfolio of marketing analytics, including marketing optimization modeling</p><p> Our modeling experts have a total of over 100 years of direct experience with marketing optimization modeling. This includes direct experience in over 35 countries and dozens of product categories.</p><p> We are dedicated to the principles of innovation, excellence and uncompromising customer service. </p><p> Most important, however, we are dedicated to getting tangible and positive business results for our clients.</p><p>ABOUT US</p></li><li><p>OUR EXPERIENCE</p></li><li><p>WAS THIS INTERESTING?</p><p> Please contact for a direct discussion Michael Wolfe, Principal</p><p>Bottom-Line Analytics LLC(o) 770.485.0270(m) 678.314.8446mjw@bottomlineanalytics.com</p>mailto:mjw@bottomlineanalytics.com</li></ul>

Recommended

View more >