Social media has become a giant tool for brands to broaden their reach and generate sales. Given the amount of time customers spend on social networking sites, it’s table stakes for any company (large or small) to get serious about investing in social media marketing. As such, it’s no surprise that a recent Duke University Chief Marketing Officer (CMO) study found that CMOs expect to invest 21.6 percent of their marketing budgets in social media within the next five years—vs. the eight percent they currently spend. The advent of social communities has fundamentally changed both our culture and the media landscape. Brands have the opportunity to have direct conversations and learn more about their customers in the process.
Given this great investment in social media, brands have an opportunity to think differently about the ROI of social media programs. Rather than thinking about the ROI of gaining a fan, think about the Return on Involvement.
This focus will be the driving force behind the shift of how brands are viewing the data behind social programs. Everyone knows there’s lots of data out there, but no one has yet to really make sense of how big data translates into business objectives. Therefore, companies need to start focusing on small data—a set of clean records that accurately record customer interaction with the brand. Small data sets can be very large, but the core difference is that big data contains everything happening in the
social realm, whereas small data sets contain records targeted to interactions with a brand.
By evaluating small data, marketers can implement better strategies because they will be aimed directly at what customers care about most. The social world is so large that you will never be able to get your arms around the entire thing—so stop trying! Just focus your energy on the pieces and parts that you can control and impact. The rest is just white noise.
A quick guide to social listening
If you haven’t been exercising your right to fast forward through commercials lately, you might have noticed a few IBM ads on TV about social analytics and how it will help ‘create a smarter planet’. Or you might have read Dell’s plans to expand their services offering with social listening for brands.
The adoption of social listening platforms has grown at a tremendous rate in the last three years, even though the technology has been around for a while. Dell didn’t unveil their famed listening command center until 2010. Why? Because it took early adopters like Dell, IBM and others to really understand how to use these platforms effectively and strategically.
When we started beta testing listening platforms back in 2006, our challenge was to cull out actionable information from a bunch of disparate data points. Key word mentions, share of voice and sentiment didn’t provide the level of granularity we needed to make actionable decisions. We knew that the human side could offer more insights than pure automation. Through trial and error, we developed a replicable process and approach to social listening that bridged technology and thought.
Today, brands have become much more sophisticated with social listening to drive engagement. A plethora of platforms are available to help with any number of the following programs:
If you are thinking about beginning a social listening program or recalibrating your current one, I offer a few tips to keep in mind.
Have a program goal in mind before you evaluate or adopt a platform.
Platforms have greatly improved their functionality and usability. However, they all have strengths, weaknesses and a breadth of offerings. Based on your goal(s), create a simple assessment tracker that allows you to look across and compare multiple platforms and evaluate them against your specific needs. I have included a sample below. Get your key questions answered along the way. Remember everything looks flashy and exciting in that first demo.
Don’t rely on data alone.
The output of social listening should be more qualitative than quantitative. Numbers give you a baseline, a cluster to investigate and a way to gauge if you are moving the proverbial needle. However, metrics in and of themselves are often interesting, but not always useful.
The real value lies in the interpretation of the results. Therefore assign a SME or partner to the project. Someone with deep knowledge and expertise on your products, services, target industries and audience personas will help make the leap from general observation à insight à opportunity.
Map out your approach.
I don’t know how many times I have heard, “Can I get a listening report?” Well, that could mean many things. Take the time upfront to figure out exactly what insights you’re looking for. Start by listing out your objectives for the program. It could be a simple list of questions you want answered so that you can:
Here is an example. Let’s say you want insights to drive your content marketing strategy for a particular product. Below are some key questions to ask:
Go beyond what is #trending now.
Mine content as far back as a year old. It may seem a little counterintuitive, but it is important to understand the development (or maturity level) of your topic areas so that your actions are relevant based on what your audience cares about. How has the social content on a particular topic or theme evolved over the course of the last year, compared to six months ago and compared to today? Have the conversations increased, stayed flat or dropped? This is where some of your metrics come in handy. Let’s look at an example below.
The goal of this particular project was to inform a content marketing roadmap in a specific industry. We wanted to create an effective content creation strategy relevant to specific points on the decision journey. We compared core topics by quarter over a year’s time. The numbers indicated greater traction for topics A and D, while B and C were emerging. By overlaying the context of the social conversation sample, we determined how they were talking in addition to how much. With aligned data points and context, we recommended that the content direction for A and D should be geared towards consideration and preference, while B and C would focus on promoting adoption and awareness. Below is a peek into what we found.
[Note: Some tools are limited in the amount of historical data they store so add this criteria to your evaluation checklist.]
Without question, social listening platforms are becoming business as usual. If you are currently struggling with your listening program ask yourself some key questions on your strategy and approach. If you are not currently listening, but know that you should have a plan in mind before you just dive in.
Have a question? I’m listening!
As you publish marketing content, you need to ensure that you have systems in place to measure its effectiveness as well as continuously improve your content marketing efforts. The best way to do this is to select and track the best key performance indicators that fit your marketing program. Typically, these fall into one of four categories:
For the purposes of this blog post, I am going to focus on the first three but you can read more about building and measuring brand advocacy here.
Automating the Curation of Content
If you have a digital marketing hub and want to automate the curation of content to other marketing sites or to CRM newsletters, the first step in the measurement process is to ensure that you have properly defined a taxonomy within your content ecosystem and that all of the content that needs to be measured is organized accordingly. Once you have that completed, you can begin to define a score for your content. I recommend using some mix of how frequently the content was:
The scorecard should assign each individual piece of content a score and be grouped together by the categories defined in your taxonomy. Not only will the scorecard give you the top pieces of content, but it can also provide insights into which content types (video, white papers, etc.) are the most popular for a specific topic.
SEO and Link Building
If the goal of your marketing program is to build domain equity, increase traffic or measure the effectiveness of your link building efforts then the approach to measurement will differ from creating a content tracking scorecard. SEO is all about traffic and keywords so your measurement process should be mapped to your SEO keywords. From there, you’ll want to track percentage of traffic to your domain by:
The SEO dashboard should focus on which channels are driving the most traffic by keyword and which are the most cost-effective. This will help you focus your efforts when creating and publishing content.
If you need to measure and increase content’s performance to conversions then you need to create a multi-leveled dashboard that will:
Start with identifying all of the places that you are amplifying your branded content. Typically these would include your social, blogs, pay-per-click and any partner’s websites. Next, organize your dashboard so that it provides a top-level review of each channel and how efficient it is a driving conversion. The middle layer of the dashboard will include details of each asset within the channel. For example, this layer would break down the social channel into your Facebook Fan Page, Twitter account and YouTube efforts. The final layer of the dashboard should provide insights into the specific metrics of each asset. For example, the number of YouTube videos posted, the number of views, traffic driven to the marketing asset from YouTube and how likely the visitor was to convert.
These are the most common KPIs you can use to measure the effectiveness of your marketing content strategy. While most marketing programs cut across all four of these scenarios, I suggest trying to narrow your focus to the specific KPI that meets your needs rather than trying to implement all of them at once. Think about what questions you need answers to and select the KPI that will help you answer those questions first. You can always add new ones as you go!
On October 18th, I-COM, The International Conference for Online Measurement held its 2012 Global Summit.
For the last year, I have had the great pleasure to represent WOMMA on I-COM’s board of directors and had the opportunity to collaborate with quite literally some of the best and brightest digital marketers and big data thought leaders that exist anywhere on the globe.
This group worked tirelessly to create a worthwhile conference framework, identify the right topics, build a structural framework for the conference, speaker presentations and breakout sessions, as well as, identify industry thought leaders that people would in some cases travel half way around the world to listen to, learn from and in some cases have a rousing debate with.
Here are some insights from the conference, in case your travel budget didn’t allow for a junket to Italy. There is a lot of content for you at this link, so surf through and pick out what you are most interested in.
Here are some high points and opinions that I’ve distilled from the preplanning work, the conference content and post conference discussions.
1. Don’t get overly enamored with Big Data. Yes, it will change how the best businesses plan their strategies but it isn’t a magic ball that will close all the knowledge gaps you have. Effective use of Big Data requires organizational alignment, special skills, tools and processes to utilize correctly. The old phrase junk in-junk out still applies, so be thoughtful in what and how you measure.
2. Dashboards aren’t the next killer app. Just like Big Data, dashboards are an efficiency tool that provide value when used effectively. Like one observer put it, “Dashboards are a lot like your highlighter in college. If you highlighted the wrong stuff in your text book, or everything in a chapter for that matter, you were sure to flunk your test. Be thoughtful in what you highlight” Just like Big Data, junk in, junk out.
3. Campaigns are transitory. Content is not. Marketers need to move their fixation from campaign optimization to content optimization.
4. Traditional activity metrics (impressions, likes, etc.) have a waning importance. With the growth and soon critical mass of ‘Do Not Track’ restrictions, marketers must move strategies and activities to ‘value metrics’, such as content and page value (and correlated KPI impact).
5. ‘ROI’ of social and in many cases, digital engagement is still very amorphous. Currently, the ‘R’ in ROI has no real, solid currency (as measured in business impact or Profit and Loss terms). Marketers need to apply more discipline to get to that before ‘The ROI of social’ has any real meaning or value.
6. Global, category standards are critical to ensuring acceptance. However, standards need not include a measure or a metric for the sake of applying one (there are a lot of measures out there that either make little sense or are impossible to track. Let’s not add to this clutter).
7. Continuing education is critical to adoption and value generation. Create, use, teach and enforce consistent, relevant vocabularies and approaches to the important general or universal categories.
8. Accept that evolution in this space is occurring so quickly that the focus should be on the process and best practices, not an end result.
Of course there was a lot more than this that occurred in Rome. Lots of detail and smart opinions were shared and discussed on topics such as mobile, attribution, multi-screen analytics, attribution and advertising effectiveness in a digital age just to name a few of the many meaty topics.
Spend some time with this information, you’ll be glad you did. Share it (or at least the eight points I’ve outlined above) with your peers and use it to continue to evolve and improve your own initiatives.
When it comes to measuring social media programs, everyone wants to know the same thing: How do I calculate the ROI of my program? In order to answer this question, you must take into account more than the simple (gain-investment)/investment equation. Simply put, you will need to look at more than just dollars invested in a program to accurately calculate the return on a social program. If you’re struggling with how to measure social ROI, start by asking yourself these three questions:
Is the conversation compelling? Content that you place on blogs and social channels has value far beyond moving a customer through a funnel. Before beginning to measure conversions, start by measuring the engagement levels of each of your social channels to determine if your content is compelling enough to generate buzz. It is social media after all—if your posts aren’t being discussed, then there’s no chance that they will drive awareness around a topic or product.
Google Analytics (especially social analytics), Facebook insights, YouTube insights, comments, shares and bit.ly analytics are all easy-to-use free tools that can help you start to measure engagement levels of your social channels.
Without the right people seeing your content, a social program will never be successful. When you’re looking to measure the ROI of a social effort, it’s important to not only measure “what’s” important, but “who’s” important as well. Use tools, such as: Crowdbooster (Twitter) and analyze your Facebook posts and YouTube and blog comments to segment users into user groups based in their engagement levels. Generating a lot of followers doesn’t necessarily translate to a successful social media program.
The final piece of the ROI puzzle is to define your business objectives before you start to make sense of any data. This is a very important step that most miss. The tools that you will use to measure your goals will vary based on what those objectives are but in the general sense, this is where you will measure conversions from your social channels. Look at your different channels to see how effective each is so that you can focus on maximizing your content’s audience response on the correct social asset.
There isn’t an industry standard or benchmark on how to measure the ROI of a social media program—that’s because every social program is different. When building your ROI measurement approach, it must include social engagement levels, conversion rates and investment dollars. Your social media effectiveness is only as useful as what you implement and the three questions you need to answer.
By now, everyone has seen this Infographic. Yes, it is complex and confusing and it should give you a headache.
The tools to manage and measure activity on a socially enabled web today are growing at substantial rate. Today, you can track and measure virtually any activity you would want to or deploy a tool to help you manage social campaigns of virtually any type. A tool or an app has been built to address almost anything you might want to do.
This explosion of social tool development, while innovative and necessary, does little to solve the bigger problems of social engagement, which essentially boil down to understanding why people act the way they act in a social brand encounter and then helping to facilitate the right engagement and then understanding in simple clear terms the value and outcome of that encounter. That’s the bad news. The good news is this will change.
If you follow any innovation curve in virtually any industry, things tend to get harder and more complex before they get simpler and easier. Why? Because, during the early phases of innovation, the processes and rules and infrastructure that will later support new inventions are getting built right along with what’s being invented. Solving any one problem on its own is the goal. Later, problems get grouped together and a new smarter solution addresses them all.
Take the Model T automobile for example. Building the car on a mass scale was one thing. Tough enough to be sure, but what about manufacturing and distributing replacement parts as those cars began to break down? Sourcing, distributing and stocking virtually every part on the car separately was likely a daunting, painful and expensive exercise at the outset, for the supplier and the consumer.
In the end, things improved. They had to for the fledgling automotive industry to remain viable. All the confusion, competing systems and supply chain gaps needed to be streamlined and refined and new smarter and more innovative solutions and options were layered on based on understanding and meeting customer needs.
Innovators moved from activity metrics (which parts are needed) to value metrics (when to make and distribute them so that inventories matched demand) as the industry evolved.
Making sure that the customer could get the parts they needed when they needed it AFTER they purchased the vehicle helped to ensure that that customer would buy another auto from that manufacturer rather than a competitor’s product.
Social Marketing today is going through the same innovation phase as the early auto industry (and every other one for that matter). It will get better. For the industry to survive and remain relevant to users, it has to! The focus will begin to move away from the tools and the activity to the experience and the value of the relationship we deliver.
As this innovation occurs over the next few years, look for consolidation to speed up and for tools become more expansive, robust…and simpler. Tomorrow’s Infographic will look drastically different than the one at the beginning of this post. It will be less about the tools available and more about content, relationship triggers and the decision journey. That’s what tomorrow’s tools will help to manage-relationships and decision journeys, not just data.
Remember, keep your eye on the prize of understanding what is driving your value metrics; what is moving your constituents through the decision process and what compels them to remain involved with your brand. The tools which help you manage your social marketing initiatives will get better, be more intuitive and easier to use, I guarantee it.
Knowing this, social marketing practitioners and their business peers need to start focusing hard on what makes good relationships work. You must now begin the process of blurring the lines between all of your brand experience channels and optimizing those channels for relevance and value.
Get ready, as the next few years will bring marketing innovation and opportunities you have never imagined were possible.
A few years ago, engagement was the holy grail of marketing. Brands delivered interactive campaigns designed to stimulate action and interaction: Take a poll, share or upload a photo, join a “community,” create a video, and so on. Unfortunately, the outcome was a lack of true engagement; brands for the most part pushed “stuff” using a variety of social and digital channels. The latest shiny tools and apps were embedded in the campaigns and for a while people did react, but few actually engaged in a meaningful way.
Today, engagement has evolved to “brand advocacy,” the art of more continuous engagement through relationship building. Boston Consulting Group describes advocacy marketing as generating knowledge and positive opinion about your brand and products by engaging individuals and small groups in meaningful, direct, two-way communication. The intimate understanding of individual consumers or customers creates both affinity and advocacy; people recommend, share, provide feedback, defend and tell you when you need to do better. Marketers have known this for a while, but few have adopted a systematic or standardized approach.
In order to excel at advocacy, brands need to understand and define their target, and find the six to eight percent who are truly passionate and want to interact, share who they are, and ultimately endorse your brand and products. This is much harder than pushing “engagement” or seeding products and hoping for return on engagement. For years, brands have collected information and data about their customers, but for the most part have failed to truly use it to develop meaningful relationships.
Both the art and science of advocate identification and recruitment has evolved significantly over the past few years. Much work has been done in understanding their motivations, how to appropriately engage, what to ask of them and what to “give” them in return. Additionally, more brands than ever are interested in exploring a path to brand advocacy. Yet as we talk with brands, we’re befuddled by how many neglect this route. Some just don’t know how to get started, while others simply don’t think it’s worth the effort.
Research conducted by McKinsey should persuade those in both camps. It studied what motivates people along the decision journey, and word-of-mouth (WOM) was paramount. The study further found that having a robust “post-purchase” channel as part of the marketing cycle was key to finding and activating loyalists who will drive advocacy or WOM.
Our own work at ComBlu bears this out. We have helped many large, global brands identify, recruit and activate brand advocates, and then engage them over time. These brands got to know their advocates, and recognized the input they gave and the WOM that they spread. Productivity among this group is dependent upon segmenting advocates and understanding how to engage specific types for defined goals and purposes. For example, a very small percentage will actually create a video or write content for you. Yet, many engagement road maps focus almost exclusively on this type of activity. Not only does this waste resources, it restricts return motivation and can lead to stagnation. Yet, many people will curate content or share it, but few brands stimulate this “collector” behavior as part of the engagement strategy. Knowing what to ask, and who to ask to do very specific things is part of knowing them and respecting them.
ComBlu defines brand advocacy as the confluence of conversation, community and content. We sponsor a Content Council for brands and almost all of the members consider content to be a powerful engagement asset. Most brands though have not mapped content to the right point of the decision journey and continue to push vast amounts of content indiscriminately into the cloud. Few have stopped to think how to use advocates to amplify it. Fewer still know how to use their content as a stimulant for conversation. And, many still think of Facebook as their hub for brand advocacy.
Social measurement is starting to get more sophisticated and allows brands to better gauge the impact of their advocacy marketing or engagement campaigns, and use the insights they glean to calibrate programs. The really smart brands use social business intelligence to better know the needs, wants and quirks of their advocates. Without great, deep relationships with them, there is no brand advocacy.
Recently Gartner predicted that by 2017, marketing’s technology spend will exceed that of IT’s within the business enterprise. According to Gartner, 2011 B2B and B2C marketing budgets as a percentage of revenue were almost three times as high (10 percent) as IT budgets (3.6 percent). 2012 IT budgets are expected to grow 4.7 percent, while all marketing budgets, in general, are predicted to grow 9 percent, and high tech marketing budgets, more specifically, are expected to increase 11 percent. On average, nearly one-third (30 percent) of named marketing-related technology and services is bought by marketing already. What’s more, marketing now influences almost half of all purchases.
So why are these facts so important (other than having more money to spend on projects)? In my opinion it is important because of the Paradox of Big Data and its impact on marketers. More money spent on IT means more data streams the marketing teams must manage, right?
Notice I didn’t say ‘information streams’?
Marketing teams can hardly keep up with the fire hose of bits and bytes, metrics, actions, activities and the like today. So how does more make it better? It doesn’t.
Think about your own work. How many dashboards, spread sheets and reports do you see? Do you have the time to study them all and make good decisions or is there simply too much and you do the best you can? Is information overload a reality for you today?
I predict that as more information systems are deployed and the more data that comes online, marketing teams will settle into two camps. 1. High intelligence/managed data and 2. low intelligence/unmanaged data.
The net result of this likely evolution will be organizations that better understand the nuances of their customer segments innovate well and deliver relevant and compelling content, products and experiences to their constituents. That’s the first group. How will they do this?
It is simple in theory, hard in practice (which is why this first group will be smaller than the second).
Members of the high intelligence/managed data group will have forged strong collaborative internal bonds between the various business teams. Marketing, IT, product development, knowledge & insights, HR will all be working together in more efficient ways than in the other group. They will have at their disposal clear and actionable intelligence that comes from their effective Big Data use. It’s important to note that this group will use much more than the standard web data we all use today. They will integrate vast amounts of other transactional information into the intelligence process such as shipping information, call center data, mobile geo-location and usage data, RFID data, etc.
Essentially, these high performing organizations will put the right filters and algorithms in place to provide them with what they need to know to perform well, not what they can know. This is a really important distinction. More data is not better. More intelligence is. Individual data streams will tell you very little. However, when they are paired and bundled together, weighted in terms of importance and linked with certain business goals, patterns and pictures emerge that provide clear insight into what actions might be taken to generate certain outcomes.
By creating intelligence filters, the paradox of big data (more) becomes the power of big data (better). When it is organized against business objective and tracked over time, high performing organizations will excell even further. They will know what activities, campaigns and assets are generating very specific business results. These teams will be able to discern between important activities and unimportant. After all, not all activities or even business goals for that matter are of equal importance.
For instance, below is a filtered report you might find in use in the first group. Note that for this business, generating revenue and driving product innovation are more important objectives than decreasing the cost of support. The question is how much more important and what activities feed into each one of these goals and how important are each of these activities? What if you tracked 800 separate activities or metrics? How would you know? If you take each metric or data stream on its own you wouldn’t.
Which brings me to the second and larger group, low intelligence/unmanaged data organizations. This group collects data like it is going out of style, many times without any rhyme or reason as to why and what to do with it. The problem here isn’t that they will continue to collect more and more of this information but that they will do so while ignoring many other forms of information that is available which can provide critical intelligence. In the end, they will bury themselves in expensive and somewhat useless information.
Customers of firms in this group will grow weary of their disjointed experiences, inconsistent content and lack of understanding of their needs. Firms that fall into the first group will enjoy the benefits of collecting these people as new customers.
There is a relatively recent analog for the potential impact that Big Data will have on marketers in the coming years and the dichotomy between the first and second group I’ve outlined here. In the 1960’s Ed Deming taught the Japanese auto manufactures how to establish and manage a quality process that turned out better parts than their American counter parts. The Japanese listened and adopted the approach, enterprise wide. The result was the reversal of market share, which had a catastrophic effect on Detroit’s automobile dominance.
Currently, neither the first or second group has really formed yet but organizations are already headed one way or the other. For marketers with the ability to be change agents, recognizing which path you are on and doing something to either ensure you remain on that path or quickly change it will impact your organization’s future success.
Big Data will either be your greatest ally or your nemesis. It is up to you to choose which.
Delivering content at the right place and the right time along the decision journey is the goal of most content marketing programs. Content is a consumable and shareable asset that has a different and distinct role at each point of the journey. Marketers need to understand each role before they can measure the impact and effectiveness of content assets.
The decision or shopping journey differs for B2B and big-ticket purchases than for consumer products or smaller priced items. For cost per clicks (CPCs), the shopping journey is shorter and often consumers have an entrenched consideration set that they brink to the point of purchase. Disruptive content is essential for breaking through and stimulating new ideas about purchase selection. The decision cycle for B2B and big-ticket items is typically longer and buyers often interact with the brand more directly and frequently.
Despite these differences, the steps on the journey are very similar. In our content supply chain practice, ComBlu uses a simple five-point decision journey, including:
· Awareness: Becoming aware of the brand, product or service with or without any intention to buy through brand communications, word-of-mouth (WOM) or independent discovery.
· Consideration: Researching and becoming familiar with a set of options that could fill a need or want. This is usually through a combination of online research, conversations, or face-to-face encounters either with a salesperson or at a retail store.
· Preference: Honing the considered choices into a short list of likely options.
· Purchase: Making the final decision and taking the plunge.
· Post-Purchase: Driving repurchase intent, as well as brand advocacy or WOM.
We use the following chart to help clients understand how to plan content type, channel selection and measurement along the decision journey. This particular version is for a B2B enterprise.
Once we understand the type and role of content along the decision journey, we can begin defining the right metrics suite for each point in the journey to track content performance and engagement trends. The following chart is a sample of a measurement-planning matrix that we use.
After we have identified the right metrics suite for the content mission at each point of the journey, we use the content module of our Social Performance Index™ (SPI™) measurement service to create a performance index for specific content key performance indicators (KPIs). This allows us to understand which topics, formats and venues perform and serve as a data point for refining the content road map and insights process of the supply chain. It allows the content creation team to be more efficient and effective when they create content and for the distribution team to calibrate their channel strategy. This approach also gives great insights into advocate participation and behavior, and can feed directly into a gamification engine that recognizes and rewards people who share, add context and create appropriate content along the decision journey.
Content marketing is a core function for today’s social business. A lot of smart people are working on new ways to socialize many of the core functions of the content supply chain. This approach to measuring return on content will evolve as the social discipline matures. How are you approaching content ROI? It’s an important discussion and one we’re glad to jump into.
ComBlu is sponsoring a free Content Masters Series beginning June 6, 2012. It’s four webinars that breakdown the content supply chain. For more information or to register, click here .Hope you’ll join us.
Content Marketing is a hot topic. Everyone wants to know how they can deliver and amplify great content that their customers will engage with. Here at ComBlu, we’ve analyzed why marketers need to act like publishers, develop systemized approach to content ideation, creation, management and measurement. In short, brands need content a supply chain. Recently, we’ve flipped the problem on its head and begun to parse it in a new way. How would you measure the quality and engagement level of your content? This will be part one of a two part series that explains how to approach a content dashboard.
Know your assets
All content is not created equally. Before we can really begin to accurately measure content, it’s key to understand what content is being delivered to your customers at each step of the decision journey. Content that is created by the brand or its customers for the awareness, consideration, preference, purchase and post purchase audiences will each have different metrics associated with them. Make sure to get organized before you begin to build your dashboard.
Align your tools
A common mistake that we’ve seen over the past eight months is that brands jump to an analytics or dashboard planning phase before inventorying the tools that are available to them. Be sure that you review what data points are available to you. I know this sounds obvious but it is a very, very important step. Frequently, the awareness and consideration content is created and maintained by a marketing team, purchase content by IT or e-commerce and the post purchase content by the customer satisfaction teams. Just because the content is on a branded website doesn’t mean that all of the content owners are using a like toolset to measure or track the content. As the old saying goes … Measure twice and cut once!
Select your metrics
Once you have verified the tools and data points that are available to you, you can begin selecting which metrics align with content depending on where it applies to the decision journey. Your dashboard needs to provide insights further than the number of impressions that you’re generating.
Here’s a preview of what’s to come on May 8th, when Kathy Baughman will reveal part two of the series which will dive into detail on aligning your metrics.
|· Volume of social content· …||· E-newsletter subscription· ….||· Reviews or stories created· …..||· Average order size· ….||· Participation in forums and discussion boards· ……|
How far along are you in creating a content analytics dashboard? What are some of the struggles that you have faced?