Data In Data Out Marketing

Transcription

1 presented by brand networks bn.1

2 Intro As the world of social media continues to expand and diversify, marketers are increasingly looking for ways to edge out competitors and streamline internal efforts. More often than not, this means turning to Social Relationship Platforms (SRPs) to manage both content and media campaigns. For most marketers, the major draw of SRPs is the ability to manage social media efforts from one hub, with capabilities beyond those offered natively on platforms like Facebook, Twitter and LinkedIn. While there is a great deal of merit in publishing posts and managing media through a singular platform, many marketers are still left wondering if SRPs are really delivering enough bang for their buck. Luckily, a new breed of SRPs is emerging. As noted in the Forrester report, Data Defines The Future Of Social Relationship Platforms, a select group of social marketing tools have evolved, infusing data into strategy, workflows and reporting. bn.2

3 Why Data Matters? Marketers face down a myriad of challenges every day, with social media strategy and tactical execution at the top of the list. In the above mentioned Forrester report, marketers were asked to describe the exact nature of their social media challenges: Gauging results was the largest hurdle, with 52% of marketers citing measuring performance of content as a challenge. Content creation was another common roadblock, as 39% of marketers noted that finding or creating content to publish was a struggle, and 35% cited deciding what type of content to publish as a pain point. Also worth noting; 27% of respondents mentioned dealing with a lack of budget for social staffing, while 14% struggled to even find qualified social media staff to begin with. To expand, data-in refers to the process of pulling in data feeds to power or inform some sort of action. Data-out, on the other hand, deals with the output of data that comes from a system or initiative. Together, the two can be harnessed by SRPs to yield more informed content creation and more results-driven measurement We believe this report paints a clear picture in which marketers desperately need a solution to streamline more informed content creation, amplification, and measurement. This is where datadriven solutions enter the conversation. Specifically, a two pronged approach that focuses on both data-in and data-out systems. 0 Measuring performance Finding Content to publish Deciding what type of content to publish Finding budget for staff to manage profiles Finding or training staff to manage profiles bn.3

4 Data-In In the context of social media marketing, data-in is most often associated with 1st and 3rd party data systems or databases, the sources for which are practically limitless. For example, marketers can harness 1st party information like inventory levels, historical sales data, loyalty program data, etc.; or 3rd party information, like weather conditions, sports scores and even US Census information. Once gathered, information from these data sources can be manually, or automatically fed into SRPs to inform anything from content creation to posting times. Once integrated, the benefits of this data-in approach are limitless. content. By looking at the right 3rd party data we can understand the influencers, outside of social media, that affect our target audiences. Incorporating this data takes a little more work, as it requires marketers to first know the pain points and interests of their target audiences. For instance, a retail store would need to know if consumers are affected more by instinct (use weather forecast feeds) or logic (pull in competitor pricing). Once this had been determined, they can pull in the correct feed to inform their product-based posts. First and foremost, this form of dataincorporation assists with marketers challenge of sourcing relevant messaging. At the most basic level, data-in can help identify both internal and external content influencers. From an internal standpoint, 1st party system integration ensures consistency between post messaging and actualities. For example, in-store inventory data ensures the correct products are being promoted, while leveraging customer data promises more accurate targeting. From an external standpoint, data-in is also beneficial to the creation of relevant bn.4

5 Data-Out Unlike data-in, data-out is more impact focused, providing insight for activities both within the world of social media, and outside of it. Data-out can be used to benchmark performance, prove-out the value of efforts, and inform future marketing strategies across a number of channels. While understanding reach and engagement are helpful to a point, marketers should demand more from their SRPs. Beyond the scope of native insights, producing data-out can shed light on target audiences, campaign performance, and even ROI. As a marketer the data-out you re receiving from your SRP should paint a complete picture of who you are currently or potentially speaking to across your social channels. Going beyond basic information like age and gender, SRPs should be able to provide statistics breaking audiences down by affinity for anything from broad categories to specific topics of conversation. This information can then be integrated into targeting efforts to help advertisers promote content to the people most likely to engage with it. Both during active campaigns, or after they have finished, data-out is integral in determining what worked, and what didn t. Breaking down campaign results by ad type, demographic, action, content, location, etc marketers can begin to understand what exactly their audiences are engaging with. This not only allows them to adjust current campaigns, but to better set-up future campaigns as well. The result? More efficient spends with greater results. Additionally, this information can help marketers with off-line efforts. Serving a similar purpose as focus groups, campaign analyses can help provide a better understanding of audience as a whole. Notoriously difficult to link with social media advertising, ROI correlations can be determined with data-out integration. By correlating social media IDs with 3rd party sales data, retailers can breakdown the predictive value of a fan. Additionally, A/B testing that aligns online media to in-store sales data can reveal correlations between message exposure and purchase behavior. This wealth of information, online and off, ultimately serves to improve future efforts while simultaneously proving out the success of current ones. bn.5

6 Conclusion As data continues to infiltrate marketing across platforms and channels, those who can harness it and turn it into actionable recommendations will rise above the competition. This process, while seemingly daunting for social media, can be significantly aided by selecting the right SRP. Platforms that encompass both data-in and data-out methods will help ensure a smooth workflow to both create more relevant content, and measure subsequent success. Contact Us to learn more: newbusiness@bn.co bn.6