Every organization understands the importance of offering consistent products and services, but most don’t understand the role content can play in delivering a consistent customer experience. Consistency encourages regularity and reliability, which in turn makes customers feel safe and open to building a long-term relationship with you and your product or service. A study by McKinsey & Company found that a consistent customer experience across the entire customer journey will increase customer satisfaction, build trust, and boost loyalty. Moreover, companies focused on delivering a consistent customer experience have improved customer acquisition and strengthened retention. Read more
What is content personalization? Put simply, content personalization is the process of delivering the right message to the right person at the right time. Unfortunately, a content personalization strategy can be challenging to define and even more challenging to implement successfully.
According to a recent survey from Adobe, 77% of marketers report real-time personalization is crucial; however, 60% report it’s a challenge to execute.
Content personalization is more than a simple ‘yes we do it ‘or ‘no we don’t’ during your content planning sessions. Building a strategic personalization plan can be the make it or break it point in the success of your content efforts.
96% of marketers agree that personalization helps to advance customer relationships and 88% think their prospects and customers expect a personalized experience.
As marketers, we can all agree that content personalization is critical to our success, so let’s dive into 3 core components that will help ensure we get it right!
1) Buyer Personas
Strong buyer personas are a balance of art and science and designed to represent your ideal customer. The most impactful personas are based on both market research and internal data analytics. Personas should be based on—and offer visibility into—the key characteristics and features of your target segments including personality, business drivers, pain points, and motivators. The most important element to incorporate in your persona descriptions is what makes your product/service appealing and clearly defines why they should choose your company over others. Identifying unique value propositions for each of your target segments makes personas actionable and will be important as you think about your ongoing messaging and content strategy. TIP: As you think about your targets, it’s best to keep things simple and start with your top two or three personas and make sure that each target is unique enough to warrant its own personalized set of content.
2) Content Mapping
You probably already develop many content types; blog posts, infographics, webinars, videos, case studies, etc., but do you know which content your targets NEEDS based on who they are and what stage they are at in their buying decision journey? Once you understand your customers (as discussed earlier with buyer personas), you can then begin to recognize the ‘right content’ to connect with prospective buyers. Your content map will include an analysis of content topic, content type, buyer journey stage aligned with each target persona, and will illustrate all the information they need to consume to move from awareness towards purchase.
3) Content Performance
Good personalization is rooted in data however, the biggest challenges with personalization are gaining insights quickly enough (40%), having enough data (39%), and inaccurate data (38%) [i]. So now the question becomes, how do you measure the utilization and effectiveness of your content? Determining how to track, analyze, and optimize your content’s performance seems overwhelming, but fear not, there are simple ways to begin tracking performance without investing in new tools or technologies.
Start with defined metrics of want you want to track and what success means for your business (opens, CTR, etc.). Use these metrics to create a baseline for current performance. Next, inventory your existing content and map against newly defined content maps. This content audit exercise will help you identify any gaps in content generation and help better allocate your resources. Finally, building a reporting dashboard to track the performance of every content asset you publish against your defined success metrics will provide real-time visibility into performance and set the stage for on-going optimization. Interested in getting into detail on content optimization? Read through our 6 Step Framework for Marketing Content Optimization.
At the end of the day, content personalization is REQUIRED to meet and exceed our customers’ expectations, but it doesn’t have to be complicated.
Keep it simple…
- Start with a defined audience (buyer personas)
- Align your existing content (content map)
- And measure results (content performance), evolving your personalization strategy over time.
[i] Marketing Charts: What Are Personalization’s Biggest Challenges and Opportunities?
In today’s marketing landscape of channel proliferation, ultra-savvy buyers, and chronic shortages of time and attention, investing in really good content might be the highest ROI decision a CMO or CRO can make. Really good content performs in a non-linear way, but what is it that makes that “one piece” drive ten times more eyeballs than that other piece? In retrospect, looking at great content, it might seem obvious, but if it were truly obvious, then why aren’t all the content pieces written that way to begin with?
So what is a CMO to do? Is there a systematic way for content optimization, aligned to buyer and influencer interest, that evolves in an agile way? In this blog post, I present a framework for creating a content factory based on both data and creativity. This is the framework we use at MarketBridge for our clients, and it works really well. It’s not software, and it is by no means hands-off, but it is a systematic method for content optimization.
The key is combining analytics and human intelligence in a process, connecting living feedback loops from one into the other and back again. Managed effectively, a fact and art based content factory like this can create, manage, and target content for high ROI in a predictable, measurable way. This blog post discusses content built for a complex, considered purchase decision, which is primarily text-based, but it can be evolved to work for both video content and pithier graphic pieces.
There are six key steps, as outlined in the diagram below. Note the horizontal line; above the line, a data-driven, machine-learning approach optimizes content, and below the line, creative minds take over.
1) Segment Your Audience by Learning Objective
The marketer today knows a tremendous amount about his or her audience. Each entry in the CRM database carries with it personal information, firmographic information (if B2B), and stimulus-response information. All of this information provides practically infinite segmentation potential for content optimization. So what does a good content segmentation look like? A good content segmentation should be based on the learning goal of the individual.
MarketBridge research shows that in 2018, considered purchase buyers are really just learners that companies intercept in their quest for knowledge. It’s now possible, for example, for a head of database marketing to learn a ton about machine learning in Python without ever enrolling in a university program, or spending a cent on proprietary software. When a good manager or executive is faced with a problem, they try to learn all they can about the problem, not immediately call a vendor.
Concretely, a software company might sell a product for insurance risk assessment. The buying entity (firm) is an insurance company, but what about learning objectives? Primary research might show that there are four primary learners in the company, along with learning objectives:
|Technical||How can I future-proof my company with new technologies?|
|Underwriting||How can I innovate and create better risk prediction algorithms?|
|Financial||What steps can I take to mitigate risk to impact my product’s bottom line?|
|Product||How can I launch new products with better risk profiles?|
It’s important to note that to do this step correctly, primary quantitative research is necessary. In quantitative research, it’s key to operationalize these segments with knowable data (data available for each lead/contact in the marketing/sales database) to be able to target actual content when the time comes. This can be done with a classifier algorithm.
There are many best practices for doing truly insightful, actionable “learning objective” research for content optimization, but these are out of scope for this blog post. I’ll try to do another post in the future on how specifically to conduct the research.
2) Segment and Score Existing Content
After segmenting buyers, it’s necessary to do the same with content. In most companies, existing content contains a treasure trove of insights. Text mining of documents using modern open source frameworks, combined with binary outcome data, provides a powerful tool for content optimization. The basic idea is simple: Understand the unique attributes of successful content for specific segments.
The key to this step is that we aren’t just interested in providing a probability score for each piece of content aligned against each segment. That’s great, but we want to go one step further and provide insight to the content creators on how to make future content better. Thus, opaque models like neural networks aren’t really appropriate here.
One highly recommended step to make a predictive content model consumable by humans is variable reduction inside of each document. It’s impossible to make a model understandable with sparsely populated variables like words. Words and phrases should be grouped thematically across the entire collection of documents. This is an unsupervised machine learning task, typically using a technique like principal components analysis (PCA). Concretely, we might end up with five thematic groupings (although in practice the number of these components will be much higher):
|Integration||API, RESTful, loosely-coupled, JSON…|
|Risk Algorithm||Logistic regression, survivor models, age bands…|
|ROI||ROI, profit, customer lifetime value, acquisition…|
|Case Studies||Results, company, individual, brokerage…|
Once this is done, each document can then be scored against these describable, knowable components, and then an understandable model can be provided back to both content writers and the marketers who are responsible for getting them to the right audiences. All of this information can be used for content optimization.
Other factors can also be brought to bear in the scoring process, other than just the overall appropriateness of the content. For example, a time element of the buying cycle can be added (cold lead / prospect / qualified lead / opportunity / final negotiation) resulting in several different “scenario” models for each piece of content.
3) Cookbook for Writers, Marketers, and Sales People
Once the model has been created, it’s key to make it truly consumable (readable) by marketers and writers. This is one thing that MarketBridge has realized is missing in the analytics space — humans really need analytics, but a lot of the time, the analytics provided are a black box. Humans are less likely to trust something they don’t understand. In the case of a sales rep, this just means they are likely to say, “I’ll go back to using my intuition.”
The components of the cookbook might include:
- A persona of each learner, describing them, their job, what they are looking for, and how to find them using knowable data
- A description of the principal components of the content repository, including plain English descriptions of what they mean, and examples of documents or specific sections of documents that typify each
- How each learner prioritizes the components
- Examples of excellent existing documents that appealed well to each learner, and why
- Key components that are conspicuously missing from the existing corpus of documents (places to focus on future content creation)
This cookbook provides the glue between the analytics team, the content creators, and the marketers. It’s also important to note that the cookbook must be evergreen, in other words, updates constantly with new feedback.
Using this cookbook, content creators can now apply their art to the facts, creating new content that is targeted and pre-optimized. Likewise, salespeople and marketing practitioners will better understand why “this specific piece of content” is great for this buyer, and will be less likely to not use it because they trust their intuition more.
4) Feedback Algorithm for Writers
Using machine learning, data scientists can also give writers a real-time tool to improve their writing. A tool like this ingests the document as raw text and then scores its likely appeal to each segment. On top of this, the tool provides specific reasons as to why the document has an appeal or doesn’t, using the components outlined above.
Concretely, feedback might look like this (with a lot more detail):
|Component||Score||Positive Terms||Missing Terms|
|Integration||77||API, RESTful…||Loosely coupled…|
|Risk Algorithm||12||Age||Band, survivor, death, risk…|
|ROI||17||Profit, cost||ROI, margin,…|
|Case Studies||43||MassMutual, Brokerage X||[All other companies]|
|Differentiation||55||Competitor A||Competitor B, C, D|
A tool like this can be used multiple times throughout the writing process for content optimization. I’m not suggesting that a tool like this in any way replaces the creativity of the writer, but it can better link facts and analytics to the writing process, while at the same time exposing blind spots that might otherwise be missed.
When building this kind of tool, work with the writers and marketers to make sure that the output is understandable and actionable. Essentially, the data science team is creating a mini product here for the marketing department. Watch them write and use the tool, and see how they use (or don’t use) the scoring outputs.
5) Create New Content
Once the factory is running, it’s important to remember to use the shotgun as well as the rifle. A rifle approach optimizes for content effectiveness based on what was learned from previous iterations of content. This is a great, data-driven approach for optimizing ROI. A shotgun approach, on the other hand, adds new, diverse information—in this case, new content—and adds this new information into the model. Another way to think about the shotgun approach is purposely adding creativity back into the model.
This is where creative marketers and content writers come into play. Gaps in content among the “training set” can be identified by data scientists, and these gaps can be addressed by writers and content creators—the “shotgun.” It is this creative process of content optimization that truly allows the model to learn and grow.
6) Rescore Based on In-Market Results
Finally, the loop is closed by refreshing the models and consumable analytical elements—content scoring, the feedback algorithm, and the cookbook—based on new content and new campaigns. The creativity of the content creators is used to expand the scope of the content model, and ultimately to drive better performance. In this way, the creative people are linked fully with the data people—and facts and art come together to drive content optimization. Done correctly, a “learning organization” forms, driving continuous improvement in marketing performance.
Overall content effectiveness can be measured with simple dashboards in a time series (overall open rate by segment and by stage, for example), showing how modeling and creativity are driving improvements over time (or not.)
A hybrid analytical-creative content optimization factory is a proven method for creating effective content. This methodology fits into a larger theme of combining human creativity with rigorous data-driven techniques.
Postscript: Out of Scope
There’s a lot that this blog post glosses over, including the specific modeling libraries and steps to use for both unstructured content segmentation, and for supervised classification of existing content. It also only deals with text, and doesn’t get into content attributes like format, video / audio, or channel. I also don’t talk at all about how to do “learning objective” primary research, which I promise I will get back to.
The Killer Slide Series on Data-Driven Revenue Growth
Let’s get tactical… In Episode 4, MarketBridge’s CEO discusses how to use existing data and content to fuel your specific acquisition, cross-selling or upselling revenue growth objectives. We get it, attempting to aggregate every data source can be complex and cumbersome. The PlayCaller™ methodology signals exactly who to target, when to target and with what specific messaging for each business use-case.
Watch how this three-step engine combines decision-making analytics with faster execution and in turn, drove $50 million in annual retention revenues for one of our biggest clients.
If you think back to middle school, getting that girl/guy to say yes to that first date meant you had to put yourself out there. Remember that nerve-wracking process? Passing a cheesy note through a friend (“Do you like me? Yes or No?”) amounted to nothing, because how could you possibly get that guy/girl to go on a date with you if you couldn’t speak to them? To get noticed, you had to do two things: (1) physically talk to your “crush,” and (2) know what you were going to say.
Marketing today is failing because we, as marketers, have forgotten that lesson. We still hide behind a friend (whose name is “Outlook”), passing anonymous emails through it to potential prospects with a campaign that still boils down to “Do you like us? Click for Yes. Ignore for No.” And the results are the same. Our campaign dashboards sit empty…
But I think we can fix this. Read on.
I believe our Sales Team is a hidden content distribution branch that is already solving for one of the two things it takes to get noticed. They are physically putting our company out there, speaking to potential customers one-on-one. THIS is where I think marketing needs to re-orient their efforts and capitalize on the face to face conversations sales is already having. At MarketBridge, we decided to take on a small experiment that led us to not only get that “first date,” but get a 17% increase in first dates (sales meetings) across the board!
At the end of 2016, around September to be exact, our CEO decided to test splitting the sales team into verticals – and by verticals, I mean teams made up of Sales VPs, reps and BDAS focused on specific industries. There were three teams and marketing was asked to support the vertical teams with content, messaging and anything else to generate industry specific demand.
The process was as follows:
- Insights & Understanding – Both teams to collectively gather insights on the industry and to run industry specific plays
- Messaging & Content – Marketing to work with sales on the best messaging and content
- Ongoing Campaigns – Teams to run campaigns – BOTH sales campaigns and marketing campaigns (I’ll explain this in a bit)
- SFDC Opportunity Planning – Planning and discussion of first meetings and demos for each vertical opportunity
- Report & Refine – Self explanatory
The first reason why this process was so different than anything we had done before is that we hadn’t worked one-on-one with our BDA team to create industry specific content in the past. This gave the marketing team extensive insight on accounts that the sales team had been working on – the industry reports, revenue reports, press releases and published content that they had been so actively digging into to understand their buyers.
Secondly, it developed a HUGE collaboration between the two teams as each week we needed to work together, hand-in-hand, to run sales and marketing campaigns. Marketing was in charge of fueling the other channels with content, but sales too had to run their own “topical” industry campaigns through LinkedIn, personal outreach including emails and phone calls. Because sales was so proactive in fueling their own channels with the content we created, it was almost like we opened the flood gates to increased content usage and views. The value of our content skyrocketed beyond a single “one and done” email promotion and social post as sales WOM brought meetings, interest, almost like we didn’t expect it to (which we should have).
Here is some insight into how all of this turned out (without letting loose any private company information):
- When comparing marketing campaigns that led to first meetings vs. co-operated vertical campaigns, we saw a 17% increase in meetings per month through co-operated vertical campaigns
- We started measuring follow-up meetings from these efforts for the first time. Before the new mandate, marketing was only responsible for “top of the funnel.” Now, we actually felt like we could see some value in the middle!
- Lastly, we saw some increases outside of “vertical” efforts. Webinar invites and content shared directly through our sales reps and BDAS led to a 60% conversion rate – the rate in which prospects went from just clicking on links to actually registering for our webinars or downloading our content. Compare that to just 13% from our other marketing channels!
Maybe it was that some type of marketing-sales appreciation was taking place… Or maybe these weekly calls gave team members additional insight in to all of the stuff we were working on and how our ideas, thoughts, collateral could be exchanged and used across all of our joint efforts… But either way, we were on to something! Marketing supports sales -> looks good on marketing!
Let’s be honest, every day you, me and your mother are bombarded by tons of marketing emails (just today I have 43 emails in my “promotions” tab in Gmail) and advertisements (whoops, just passed by the 10th one on my Facebook feed) that no one seems to take notice of (ok, you might actually click on ads here and there). It’s not that the content we are creating isn’t good… it actually is! It’s that we are using the same old exhausted channels that everyone is using to market. 21st century consumer demand is built by being 1-on-1, personalized and relevant. This is where we will see sales begin to have the upper hand in demand generation over marketers.
Unless, that is, marketers focus more of their efforts on enabling sales, and making sales teams their advocates.
If you are an organization in which your marketing team IS CRITICAL in generating top of the funnel leads, what I said above might not apply to you, but consider the illustration in the chart below. Your leads mean nothing if sales can’t convert them. Your content distribution framework has to push the buyer toward a path-of-sale, meaning SALES needs your content too. Collaboration, more relevant content creation and working one on one to understand what is worth creating and what is not, will do wonders for your content ROI…
Would love to hear your thoughts in the comments below.
I finally justified to my wife why I bought $200 Nest thermostats a year ago…
After receiving a heating bill that was double what we were expecting, I jumped into the metrics that Nest thermostats provide. Immediately I saw the problem… the heat was coming on repeatedly during the night (see Energy History below) during a time period we least needed it – A) our bedrooms are all upstairs where heat is trapped and B) we have heavy down comforters on our beds that essentially cook us in our sleep. (My wife would dispute that.) The translation? I was spending money on heat I didn’t need, and wasn’t even aware that this was a problem until I dug into the details.
The reality is that, in all likelihood, a similar situation is happening to you. Only, rather than heat, the money is being lost on pitfalls within your content creation and management process that are invisible to you.
According to a recent study run by Kapost and Gleanster, the average enterprise organization sees $0.25 of every dollar spent on content marketing efforts lost to various inefficiencies.
That’s actually A LOT of money when you break it down! Keep on reading…
Estimating Lost Content Spend
If we use the latest Gartner CMO Spend Survey, an enterprise company realizing $1B annually in revenues likely carries an overall marketing budget equalling about 12% of revenues. And if we lean back on the Kapost/Gleanseter survey mentioned earlier, an organization of this size is likely averaging about 55% of that marketing budget against content marketing efforts but seeing a waste of nearly $0.25 for every dollar spent. Let’s break that down…
- Company Size in Revenue: $1B
- Assumed Marketing Budget: $120M
- % Dedicated to Content Marketing: $66M
- Projected Waste: $16.5M
There’s your “heating bill” surprise… nearly $17M in marketing costs that would be considered wasted spend!
Obviously these figures are based on survey studies where you would have to plug in your own numbers, but the question remains, where are these dollars being lost? Is there a way that we can, in a sense, create a “Nest-like” analytics overview that helps us determine where our dollars are going out the door? I think the answer is “yes.”
At the risk of this blog article becoming a little numbers-heavy, allow us to make some further assumptions that can supported by the research studies already cited:
- Avg Number of Internal Resources: 15
- Avg Salary for Internal Content Resources: $60K
- Percentage of Time Against Content Creation: 62%
- Avg Hours/Month For External Resources: 130
- Avg Rate for External Resources: $130/hr
Using these numbers, it’s relatively easy to determine a blended FTE ($79/hr) which you can then project against the various types of content you might be creating using benchmarks of time/piece to create. Ultimately this yields what your investment is for each type of content which I would like to label PRODUCTION COSTS.
Then, assuming we can make educated guesses (or use available content analytics), we would be able to determine how much of the overall company revenue was influenced by content and segment that down to influence by content type. This would afford us a value per content type labeled as UTILIZATION VALUE.
Plotting these two values against one another would yield a nice quadrant matrix showing us which content was costing you the most to create, but not returning you any value in sales utilization. The output would look like the following:
Based on this illustration, the upper left quadrant is the equivalent of my Nest analytics chart. These content types are where you are unnecessarily “heating the house.” Your videos, ebooks and webinars content would either need to be audited for value, or you would simply stop spending resource dollars on them.
Here’s the thing. Arriving at the values to give you this type of insight is not that difficult. Internal resource spend is merely an internal audit exercise. For content utilization, you would simply need the right analytics for determining content utilization by sales as they go after their sales quota.
We’d be happy to build the analytics that allow you these types of insights. After all, if lowering your heating bill is a priority for you at home, isn’t lowering your content bill an equally important goal in your marketing leadership role?
Content is king… or so they say. But the hardest part is effectively measuring it’s return on investment. Whether you are in manufacturing, technology, healthcare, banking, or another industry, the problem is apparent. A recent study from Sirius Decisions states companies are spending tons of money on content; small companies – $175,000, medium companies – $4 million and large companies – $8.2 million.
Here’s a question to ask yourself: Is that content getting used? Beyond marketing, is sales using it?
While we know that you and your teams are already well underway on your content strategy for 2017, here are 3 harsh realities that many businesses need to recognize they face and find a solution to fix them.
Content is Scattered Everywhere.
In our discussions with clients across various industries, the biggest and most simple (yet complex) problem is content is everywhere. From your Sharepoint site, Dropbox, local computers, hard drives and more… it’s long lost most of the time. On top of that, how do you know if the content you have in hand is the most up to date? More than 60% of marketing collateral goes unused by B2B sales reps, at a cost of nearly $2.3M per year for 3 reasons:
- They don’t know it exists
- They can’t find it
- It’s not relevant to their buyer
Lesson: A single easy-to-access location (for BOTH sales and marketing) is key.
Content Tagging is Time Consuming.
Oh, the dreaded task of content tagging – you hate doing it but you know you have to as it allows for your sales team to be able to filter and find the right content for each buyer conversation. It’s a time intensive process and in addition, who knows if the tags you decide to use are really the right ones?
Lesson: Take the time to tag your content but keep it down to the most relevant tags for filtration – whether it’s categorizing against buyer journey, product family, vertical, or content type. By allowing sales to filter and find the right content in each buyer decision they in turn help potential customers make decisions at a faster pace.
Content Performance is Hard to Measure.
Many marketing teams have little to no visibility into which content performs best (or worst) to improve their processes. And when it comes to the content creation, the question you constantly ask is “is my content spend appropriate?” You know 50% of your content is useless, the problem is, you don’t know which 50%.
Lesson: Understand how your sales team, prospects and customers are accessing and using your content. Know which content is being viewed and how often. All of this will help you decide which content to reuse or change to ultimately reduce costs and see increased ROI.
As virtually every marketer has heard, producing great content helps drive awareness, builds trust with customers, and improves lead conversion. For FinServ, Content Marketing is critical to building relationships and trust, and helping to educate customers on what are often very complex product offerings. But, knowing WHAT to share out of all of the types and topics of content you’ve provided is critical to selling success. There are a few challenges today though:
- Regulatory environment creates new risks for financial services firms as content marketing gains traction. The multi-million dollar fine for sharing non-approved content is something businesses need to avoid.
- Too many FinServ firms are leaving content distribution decisions in the hands of their sellers. Yet, the average RM/Wholesaler finds it extremely difficult to know what to share. The best businesses are making much more prescriptive content recommendations.
- Because FinServ firms have jumped into content marketing, they are investing millions of dollars on content creation WITHOUT clarity on what works, where they get ROI, and what to stop producing. Measuring content impact is challenging. As a result, this costs FS firms millions of dollars in waste per year.
Financial services firms need these three things when it comes to content:
- Ability to make better investments in content given the large amount of resource and regulatory constrictions concerned with building content in these environments.
- Ability to use content to enable the RM/Wholesaler to build trust with the end customer. This means investing in platforms and intelligence that allow for RM/Wholesaler easy access, AND giving prescriptive direction on which content is best for what use.
- Ability to understand what content works, what is converting, what people are using, ROI, etc. through to the sales transaction
How do you get content to your sellers/agents/wholesalers? Do they use the content you provide them? Would love to hear your thoughts.
The demand for “big data” and “big content” to better acquire, retain, and cross-sell B2B customers is growing rapidly. Since 2010, most B2B companies have made significant investments in four core types of customer engagement platforms:
- CRM (e.g. Salesforce)
- Marketing automation (e.g. Eloqua, Marketo)
- Content management (e.g. Adobe)
- Social media (e.g. Linkedin)
These platforms have enabled companies to make quantum improvements in workflow efficiency by automating labor-intensive marketing and sales tasks. But increasingly, executives are trying to grapple with an even larger potential benefit of these technologies – the explosion of customer data and content. The new B2B challenge is helping product marketers and front-line sales reps increase sales effectiveness by “cherry picking” accounts and customers that are most ready-to-buy and providing them with the most relevant content and offers.
To address this challenge, from 2012-2015 venture capitalists and private equity firms invested billions of dollars in 100s of small, innovative SaaS companies specializing in predictive customer analytics (who to target) and content personalization (what to offer). As B2B Sales & Marketing organizations have tested and on-boarded these data-driven marketing and sales effectiveness technologies, three critical lessons have emerged:
- Successful predictive customer analytics processes – those that actually enable sales reps to target the right prospects and book revenues – require aggregating and analyzing customer data from both external and internal sources
- Successful content personalization processes – those that actually serve unique content/offers tailored to each prospective buyer – require curating and measuring the performance of content from both external and internal sources
- Successful deployment of these analytic technologies – the who, what, where – must be easy-to-use and be trusted by the Marketing and Sales professionals who use them
Working with our enterprise clients, we are seeing leading CMOs, product marketers, VPs Sales, and quota bearing reps all rapidly migrating together toward digital sales enablement solutions. Our own customer intelligence platform we call Playcaller is just scratching the surface of combining “big data” and “big content” to enable both B2B product marketers and quota-bearing sales reps to better determine who to target, where to reach them, and what content to offer. By combining deep customer insight and personalized content, we see our clients build high performing, data-driven, end-to-end marketing and sales processes to maximize the performance of any “sales play” — customer acquisition, cross-sell, or retention.
The lesson is simple: effective Marketing and Sales processes need BOTH predictive customer intelligence and personalized content. Like peanut butter and jelly, they go together.
What do you think?
As sales leaders, we spend a lot of our time trying to figure out how to make our sales teams more productive. Selling into the sales and marketing technology space, MarketBridge sees many of our clients and peers struggling to do the same.
Through that observation, an interesting and counter-intuitive trend has emerged. In an effort to make sales reps more productive, we as leaders have heaped more and more technology, data, and process on their laps and the result is far more complexity for our reps than we even realize.
Combine this with the fact that the average buyer wants less interaction with sales reps and more with online resources and tools to help them make decisions. The job of the rep is significantly harder than it has been in the past.
As evidence, I point to three examples from our Fortune 1000 clients:
- Buyers are increasingly opting out of engaging with sales reps as frequently nor as early in the sales cycle. Customer journeys are mainly on-line, self-educating without sales engagement. So the plays we have run as a sales reps are just not working. And the tools we “need” to use to learn about customers take up all our time. The “table stakes” buyer research that our customer expects us to know to show that we are well prepared is a huge time sink and takes away from valuable selling time where we can deliver value and insight. As a result, customers report that only 29% of the sales calls they have with suppliers are valuable.
- Content is king and customers expect this as part of how sales engages.But as a result of trying to deliver perfect insight to each buyer, reps struggle to find the right content to share with any given buyer. One company we looked at found that reps spend 40% or more of their time trying to figure out what content to share, and where to find it. Another implication of the new buying journey … sales reps now need to manage content. Marketers are not helping here; instead of making it easy, they tend to add complexity for the rep.
- Sales reps now have tons of customer data and analytics at their fingertips, including hundreds of data sources and, for most sales people, at least 7 separate apps or tools on their desktops. One large technology company we have worked with was using 11 different tools. Imagine that…to do our job “right”, we as reps need to spend most of our day logging in and out of a set of tools to get data and insight on our customer. What do we do? Well, either we stop selling or we stop using all the tools. Neither is a good outcome for the sales leader. You are either losing opportunity or wasting sales resource.
So what can sales leaders do about this?
In the words of Wayne Gretzky – they have to “go where the puck is going to be, not where it is now.” Anticipate what the world could look like 2-3 years down the road and start putting the building blocks in place.
At the most basic level, focus on:
- Empowering sales reps with a single, useful, consolidated set of customer buying signals (data plus analytics) as opposed to the multiple random apps and data sources they have now
- <Connecting sales reps to buyers growing on-line activity, as opposed to email spamming prospects and having no clue what they are doing on-line
- Enabling sales reps to digitally engage buyers in addition to traditional phone or face-to-face sales calls as opposed to doing thousands of costly outbound dialing for dollars
If you get these things right, you will improve sales performance and reduce cost. Sounds simple, right?