Brain Vibe

marketing muses to stay engaged

Data Governance More Than Ownership

When kicking off data management initiatives a large and key component is establishing the data stewards that represent the data that is collected, managed, and leveraged in business intelligence.  By having these data stewards, and subsequently a data management committee, companies feel safe that the proper data governance practices are going to be put in place.  Not so.  Ownership (=Stewardship)  does not equate to governance.

Many factors contribute to governance and business boundaries can quickly be broken down if you approach governance in business silos.  As you walk through your process of data collection you’ll quickly find that what is considered the preferred source of data may not be generated by the team that determines what should stay, what should be modified, and what should go.  In fact, depending on how you view the data, conflicts arise as to what is considered accurate, appropriate, of the contributing factor in decision and business point of view.

This is something I’ve run into recently when building a business intelligence solution for web analytics.  Even within my own department of advertising executives, views of what transactional data should be considered the record of source is up for grabs depending on who is the recipient of the information and how it is used.  Levels of accuracy vary depending on when data is needed, how it may be used for marketing optimizations, or if it will be used to actualize spending for billing.  Throw into the mix that data feeds coming from vendors are constantly changing as they actualize transactions over the course of days, weeks, and even months, and finding the truth in the data becomes a challenge that defies religious opinion on the subject.

Sorting through the challenges of governance to determine what makes data reliable requires looking at a variety of factors and allowing for multiple views and uses.

  • Reliability of source
  • Time of collection
  • Actualization
  • Business process affected/use of data in decisions
  • Degree of accuracy required

If you will notice, I do not include ownership.  This is the artificial governance.  Ownership in establishing governance only serves to create a framework around the above factors that creates credibility.  Ownership, and then the transformation to stewardship, serves to continuously monitor, enforce, and improve governance around data needs.

Start your data management off on the right foot, don’t confuse ownership with governance.


Filed under: business intelligence, data quality, , , ,

Web Analytics: Caught Up In the Click

When I talk to my fellow search and online display marketers about web analytics, they look at me like I have two heads and crossed eyes.  They focus on optimizations made at the conversion – its the old marketing funnel. I care about who is converting and who is not.  Internet marketers say, “Who cares if you hit your target conversion volume at the right price when they could be the people that will leave you in a heart beat rather than be real customers with ongoing revenue?  Customer satisfaction, customer retention, that’s the job for Customer Service.”  Well, you should care.

Internet marketers need to think like their program marketers.  They need to be asking the same questions and align to their organizational goals.  The way to do this is through analysis of converter profiles and behavior analysis.  This way you do what we all say we should do:  target the right people, at the right time, with the right message/offer.  It isn’t enough to drive volume, you want to drive quality in that volume.  It is much more expensive to acquire new unfamiliar customers than it is to convert those that are already considering you or are you customers.  This is true whether it is internet marketing or offline marketing.  Why convert customers that will make a small purchase, then dump you later when you can convert a customer that is interested in your products now and later on?  Keep the short-timers in the mix at an optimal rate to maintain revenue, but it’s the long term customer that will be profitable in over time.

Think about your over arching marketing plan.  A key component is who your ideal customer is and how do you bring them in, keep them, and grow their value.  Somehow this is getting lost when you put in your big ad spends on paid search and display advertising.  In the tactic, the measure is at the ad group, placement, key word, creative, offer/call-to-action.  It is all about optimizing increases in conversion volume to site at the lowest cost.  We need to flip this over and go back to also looking at if we are converting the right people.

Converter Analysis

Take your campaign analysis down one more level.  Look at who is making a purchase on your site and what they are purchasing.  Are the purchaser profiles aligned to your broader targeting strategy?  If you were going after 30-something new mothers in affluent metros, were a high proportion of those purchases in this group, or were they 50-something grandparents in retirement communities?  The first may offer repeat purchases as new mothers will continue to purchase items over the growing years of their babies.  Grandparents or relatives may only complete a one-time purchase for the baby-shower.  You’ve already done the research to say where to get the most opportunity short term and long term, make sure your internet marketing effort supporting this.

Behavioral Analysis

Now that you know what your converted customer looks like, move upstream to their internet behavior.  Analyze your ad groups and key word searches and compare customer segments.  Recognizing attribution as it pertains to segment targeting will allow you to optimize more surgically.  On the surface particular tactics may appear to be driving the greatest conversion.  But, this may not be the case as it pertains to who you want to attract.  Through behavioral analysis you’ll better position your ad spend for behavioral targeting and optimize your online display dollars.

Becoming a better internet marketer is as much about effectiveness as it is about efficiency.  Effectiveness comes not only from volume of conversions but having the right volume of quality conversions.  Optimize not only to the volume.  Optimize to the segment you wanted to reach in the first place.

Filed under: business intelligence, Lead management, metrics, Web Analytics

Marketing Measurement Primer: Creating Your Reporting System

So, you are thinking about creating an automated reporting system to monitor marketing performance across all your activities: direct, website, internet marketing, social media, e-commerce.  There are all these great tools out there with shiny dashboards and promises of business insight to drive your decisions in one place.  STOP!

It is not as simple as recreating your Excel spreadsheets in a database and copying the graphs to Powerpoint.  Forget what your analysts tell you.  The data isn’t the most important thing in this process.  Your business rules governing your data is the most important.  The business rules stem from your process, your plan, and the point of view of your business.  Make sure your establish your marketing plans and business rules as the cornerstone to your reporting needs BEFORE you go right to the data.

Most business intelligence projects are emerging from mature processes and the topmost functional areas that have application systems capturing and storing data as it happens.  There is a consistency around data elements.  For instance, finance, sales/marketing, customer service all work off customer data with sales transactions and relationship inter-actions.  The reason is that the application manages the data.  Where this breaks down is in the new world of cloud computing and SaaS solutions managing micro components of your business.

Your headaches in understanding marketing performance stems from this increasingly disparate view of your activities.  Traditional marketing is housed in your CRM system (ex. Siebel, SAP).  Website marketing is house in your web analytic suite (ex. Omniture, Webtrends).  E-Commerce might be managed with your E-Commerce provider.  Interactive marketing may be managed by your ad service (ex. MediaPlex, DART) or Google.  Each of these services have their own discrete view of the world and provide you with canned reports.  First and foremost all these various systems need to be bring data into a central repository before any consolidated reporting can happen.  This is where most reporting projects begin and move right to the reporting design and implementation.

Be careful.  This is the pitfall.

What makes the reporting in these disparate systems work is the business rules and processes that generate the data.  How a campaign is set up and tracked in one system can be very different than the other.  Cost management will vary by activity as well as marketing cost may be flat fees or operate through exchange systems with different billing methods (ex: by time, conversion, packaging). You want your campaign plans enforcing the management and reporting of activity across all marketing channels.  If you have not created this framework, you risk accuracy and completeness as feeds can have issues in delivery or have conflicting data that needs to be reconciled and/or adjusted prior to reporting.

As you begin your marketing performance reporting project, bring your sample reports and spreadsheets to the table during business analysis.  But, you also want to be sure you bring your marketing plans and business rules to the table as well.  This will ensure accruacy of reporting and mitigate issues in design, development, and implementation of your new dashboards.

Filed under: business analytics, business intelligence, marketing technology, , , , ,

Social Media and Website Engagement as Business Outcome or KPI?

What is it that we really want to know when we are measuring social media engagement?  It can be an indicator of advocacy, brand affinity, purchase consideration, or actual sales.  In many cases, engagement is considered the outcome showing the value of brand.  The problem that arises in this is that all to often how it is measured has nothing to do with how the value of the brand translates into customer value or initial purchase.

The first problem is that measuring engagement often has more to do with the amount of time spent on site and the amount of view, clicks, and level of content reached.  On the surface, this is a great first step.  When looking closely, flaws abound.  The reason, what is the online experience trying to achieve?  If the purpose is a landing area that drives purchase conversions, then more time on the site and an increase in pathing may actually be an indication of less qualified visitation. If the purpose is education and a first step into creating a customer relationship, then more time on the site, activity, and depth of knowledge seeking can be a good thing,  However, to be realistic, have you looked at your SEO and SEM statistics lately?  My guess is that around 70% of those visiting your site are direct visitors or searching on branded keywords.  That being the case, visitors already know a good deal about you prior to coming to your site and the more time and research they do might also not be a good thing if they are comparison shopping.

Sounds a bit dire, right?

To counter this, web analysts are starting to take a look at measuring actions as they relate to conversion.  Simply spending time on the site, views, or measuring clicks isn’t considered viable and predictive.  However, if desired actions are achieved such as downloading high value content, sharing content, participating in discussions, or taking actions that are highly linked and indicative of purchase behavior, then tracking at this level is more valuable.  Actions can be more connected and aligned to desired results and predict conversion.  Right?  Maybe.  The issue arises of clearly understanding actions that predict conversion to sales or customer value.  The other issue is that measuring the number of actions also isn’t that far off from measuring page views, clicks, and time spent.  It might be more meaningful in that it is a validated initiative, but again, is more actions a good thing?  Once again, as with traditional metrics, at the end of the day, what is your site or landing area intended to do?

Measuring engagement should actually take into account both methods for a hybrid approach.  How this hybrid is determined once again depends on what your desired outcome for the website or online experience should be.  At the simplest level, starting with actions taken and tracked as the foundation of a predictive model is a more sound approach.  These are steps in a desired process for conversion, regardless of what your conversion intent is, that are reliable and accurately measured.  However, actions are part of a process and thus need to be ordered and weighted accordingly.  Processes are relatively linear in fashion and assigning a weight based on the step in the path is important.  It can be a simple distribution or multiplicative, but a step does have relevance and weight.  In a hybrid approach, we also want to introduce the traditional aspects of views, time spent, and clicks.  Starting with views and time spent, leveraging these as coefficients in the model will provide a better perspective on weight on desired actions and ultimately the desired outcome.  Essentially, views act as impressions that influence behavior and time spent introduces the amount of exposure necessary to trigger a desired result.  Taking from online display advertising effectiveness, banner ads as an influencing factor for awareness and conversion increases with exposure even if no action is taken to click through.

That leaves clicks.  This traditional metric introduces a duplicity element that needs reconciliation.  It is important to carefully introduce this measure into the model as it can inflate engagement metrics and thus over forecast results.  Clicks also can be an issue as it is typically a component of measuring effectiveness of ad spend.  What needs to be determined is if the click is associated to intended actions taken on site and avoid double counting or inaccurately measuring ROAS.

Ultimately, engagement is an indicator of a desired outcome and not the outcome.  Combining traditional site tracking methods to weight and adjust models predicated on process actions will create a more accurate predictor of outcomes.

Filed under: business analytics, business intelligence, metrics, social media, social media marketing, , , , , ,

B2B Lead Nurturing is Not Linear

Lead Nurturing Lead PassIt is much easier and cheaper to work with people that know you than it is to build a new realm.  That is what many marketers and companies are realizing as they shift marketing investment.  Lead nurturing is now more important than ever.  Yet, if you analyze your database, what does lead nurturing look like?  When is a lead qualified to truly enter into the sales cycle?

Demand and lead generation steps have typically progressed from response to lead pass without adequate filtering or analysis that a lead is ready to engage in the sales process.  This has hurt marketing’s credibility in generating real value to the pipeline.  It has put the work on sales to ‘clean’ the database and have them focus energy on leads that aren’t interested or ready for personal connection and may be of lower value than cold calling.  Additionally, some companies try to alleviate this by adding a telemarketing stage prior to a lead pass to personally assess and qualify a lead for the pass.  This can be a costly investment for marketing if again, it is putting leads into this step of the process before leads are fully baked.  Yet, that doesn’t have to be the case.  Properly analyzing and defining leads or groups of leads by their activity within an account can offer sales insight that puts them closer to the opportunity.  This is where lead nurturing can be a strategic effort rather than a tactical process.

Traditional lead tracking reports show a linear funnel from response to disposition within a campaign or program which mimics the linear aspect of the lead process.  In reality, leads have most likely been associated across campaigns, social media marketing interactions, organic web visitations, and even events or interactions with sales and other organizations.  How leads interact, where they go, the frequency, and topic concentration tells you a lot about how ready they are to enter a sales engagement process.  Additionally, compared and correlated to other leads within the same organization, you get a good picture of account readiness and opportunity.

This analysis in many cases is conducted to create target segments as launch pads for new campaigns.  Leveraged within a lead nurturing process, it can be the used as the decision point for when it is best to pass a lead to sales.  It becomes what qualifies the lead to move on vs. relying solely on a single response point on its own or in a linear context.  In fact, analyzed properly, reports and dashboards can be provided to sales that provide a picture of high opportunity areas within their accounts that they may not have seen.  For instance, an up-tic in white paper readership and participating or scanning of social media marketing content on products within an account might provide account managers early warnings that companies are assessing new solutions.  By having a report that provides context on the customer relationship provides sales a greater ability to pick up on the lead nurturing process without having to wait for marketing to pass the lead themselves.

Today, leads are classified as meeting minimum requirements of responding to a campaign and having check boxes of information filled out.  Lead nurturing is really about understanding interactions with your customers and how those interactions are indicators for next steps in the relationship.  Analyzing and recognizing patterns within your contact and account databases is more than identifying segments for targeting new messages and offers.  Used strategically it can be a transition point in your lead pass process improving your ability to generate business and reduce resources and budget through better focus.

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Filed under: business intelligence, crm, Lead management, , , , , , , , , , , ,



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