This document discusses omnichannel marketing and the importance of data quality. It notes that accurate contact data is key to driving omnichannel efforts. However, many companies struggle with collecting, consolidating, and using accurate data across their different marketing channels. The document provides some ways for companies to immediately improve their data quality, such as setting up a strong data foundation, integrating data sources, and starting with a simple test to cleanse data. It also shares examples of how companies have enhanced their brand and driven exceptional customer experiences by improving data quality.
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Lauren:
Hi everyone, thanks for joining us on today’s webinar. We’ll be talking about how you can build a successful omnichannel marketing experience through good data quality.
Before we jump into the meat of today’s presentation, I have a few housekeeping items before we get started. Please note that this webinar is being recorded and a copy of the recording will be sent to the email address used at the time of registration. If you have any questions, please enter them into the chat box located within the BrightTalk platform. We will be monitoring throughout the presentation and will cover off any questions at the end.
Lauren:
Johann and I will be speaking today.
Johann is a key account executive and in his job, he hears a lot about omnichannel initiatives, especially among retailers.
I am a marketing campaign specialist and I work a lot in our hero channel—email.
But that’s enough about us. Let’s go into the agenda.
Lauren:
We’ll discuss the overall landscape of omnichannel marketing and how data drives all of those efforts, see what the biggest challenges are, and then finally give you ways to drive accurate and high quality data right now, not at some distant point in the future.
Lauren:
Okay! Let’s start with the landscape.
Lauren:
Before you get into what something is, it’s sometimes more helpful to distinguish what it isn’t.
I’m sure you’ve heard of omni, cross, and multi-channel marketing before. But what are the main differences?
Multichannel marketing is using multiple channels to engage prospects and customers. Some examples are brick-and-mortar stores, call centers, and websites.
Crosschannel marketing is creating a seamless experience across those multiple channels. An example would be a customer ordering something online to pick up in-store and not running into any disturbances when they go in to pick it up.
Omnichannel marketing is basically multi- and cross-channel done well. It’s creating a consistent and seamless experience across all channels.
Lauren:
Here’s an example. Say a customer enters a store with a smartphone in hand.
Successful omnichannel marketing would be if her in-store experience was personalized with recommended offers or special discounts based on what she was looking at using other channels. Her experience should be consistent throughout.
But what drives all of that? Lots of data, and in particular, lots of contact data.
What we’ll get at today is how to use the data collected from multiple channels for cohesive omnichannel marketing.
Lauren:
So a question for you, listeners. What is your most commonly used channel to collect contact data?
Lauren:
…So those results are pretty in line with our own global research survey as well. Our research shows that websites, sales teams, and mobile are the most commonly used channels, and also that U.S. companies use almost 4 channels to collect data. But the more channels you use, the more room you leave for error.
So we’ve looked at the different channels used to collect data. Now let’s get into why it’s important.
I’ll pass it off to Johann to speak about that.
Johann:
Why is this important? Because of the single customer view
State why single customer view is so important (e.g. key driver of omnichannel success)
Set up the stage for the challenges of omnichannel marketing on the next slide (read talking points below)
The reason why people are making a big deal about omnichannel marketing is because it gets you to that single customer view.
The biggest challenges in omnichannel marketing after collecting accurate data are integrating it into your CRM and being able to use it. If you do all three successfully in your omnichannel initiatives, you can get to a single customer view.
Shameless plug, but our technology helps you distinguish who’s who in your database. Relate back to namesearch or PiQ in terms of getting
A single customer view is basically what all B2C businesses want to get to. Why? The obvious benefits are higher conversion rates, better customer retention, and an increase in customer lifetime value. And the only way to get all these benefits is by providing value to customers in your omnichannel marketing.
But the first problem in all this is sifting through all that data and figuring out who your customers are. And when you’re collecting data from all those different channels, this problem can be a huge obstacle.
Two simple things you guys can do right now is: 1) Write down all the points where you collect data from and 2) Write down how you currently integrate data from your channels. That’ll help you organize dataflow within your business. We’ll get more into that later on.
Johann:
Like we said in the previous slide, the biggest challenges in omnichannel marketing are
Collecting accurate data
Consolidating that data into your CRM
And using that data to really know your customer
Getting over these challenges will help you create the personalized and consistent brand experience necessary for profitable growth.
Johann:
As part of my job, I hear a lot of concerns from retailers about omnichannel challenges they’re experiencing. One of the most common is definitely that they still don’t have the technology or manpower required to perfect omnichannel marketing. So think in terms of technology not being advanced enough or there not being enough people who know how to really use that technology within the business to perfect their omnichannel efforts.
Johann:
We’ve gotten into this briefly in the past slides, but now we’ll get into how omnichannel efforts are really driven by data and the impacts of what bad data can mean for your omnichannel marketing.
Lauren:
Contact data drives everything in your omnichannel initiatives. No argument there. But let’s take a look at emails in particular and walk through this short example.
In a group of 10,000 people, what’s the likelihood that someone will have the same name as you? Maybe 20. Now, what’s the likelihood that someone will have the same email as you? None.
Marketers often use email addresses to drive omnichannel marketing because they are the most reliable differentiator of an individual we have in the marketplace. We’re calling out email in particular, but this scenario can apply to other pieces of contact data as well.
When you collect unique identifiers like emails, the trick is to use technology to drive omnichannel efforts even further with that information. It’s like what Johann was talking about earlier with consolidating contact data across your channels or using that data to make more targeted messaging.
Lauren:
Now we know that accurate contact data is the lifeblood of omnichannel marketing.
Too often, the omnichannel dream falls flat because the data behind it isn’t strong enough.
Now we’ll go into the key data challenges that affect omnichannel marketing.
Lauren:
The first data challenge is the collection of accurate data. Marketing activities like email campaigns, direct mail, and person-to-person contact all rely on it.
Like we stated earlier, accurate data collection gets harder with the more channels you have. For example, one of the predominant ways marketers seek to communicate their omnichannel message is through email.
However, 78% of companies have issues with email deliverability. That’s huge! This shows how accurate data directly affects omnichannel initiatives.
Think about it. If one of your sales reps accidentally mistypes a domain name, marketing emails you would send to that customer won’t get delivered and you’ve failed at the first step in your omnichannel marketing.
One of the ways you can address this is to think about real-time or batch validation solutions.
(source for stat: http://marketingland.com/email-marketing-takes-highest-share-of-marketing-budgets-38386)
Lauren:
The second challenge after collecting all that data is consolidating it.
72% of marketers find data fragmentation as their greatest challenge.
More likely than not, you use different technologies for data collection. Not only does that confuse people on where exactly to search for this data, but if and when they do find it, they might encounter trouble with duplicated accounts.
Consider this scenario: Let’s say you don’t have technology that dedupes customer data. Therefore, you could have multiple accounts for the same person. That can really affect the effectiveness of your marketing efforts.
A tip would be to do a simple customer search right now in your CRM and see if there is duplicate contact data anywhere. If there is, you should research solutions that have matching and deduplication abilities.
Lauren:
The third challenge behind omnichannel marketing is knowing how to use that data.
Call out the 90% stat above
Are you using all the contact data you have to gauge the likelihood of customers engaging or converting?
Are you able to see that someone who bought something from your website and returned it three months later is the same individual?
These are important questions you should answer.
Johann:
Now that we’ve gone over the main data challenges behind successful omnichannel marketing, let’s get into what you can do to improve your data quality right now.
Johann:
There’s one thing you can do right away: Figure out if you’re validating data at all. And then figure out if you’re doing it in real-time, or if it makes more sense to do a back-end bulk cleanse of the data already in your database. You have to get your foundation right first to make sure the rest of your omnichannel initiatives are solid.
For example, 22% of companies directly tied lost revenue to lost data. And that’s just one example of what a weak data foundation will have on your business.
Something to keep in mind is that neither real-time or back-end validation are better than the other. Both are important to maintain the most updated and accurate information possible.
Johann:
Aldo had no front-end address verification solution, resulting in mistyping, accidental address omission, and duplicate customer accounts.
They implemented a front-end, real-time address verification in their ecommerce and POS and have seen an increase in the number of accurate and deliverable emails in their database and a decrease in the email bounce rates. Now their customers receive welcome emails right away, which improves customer perception of brands.
Tie it back to strong data foundation (from previous slide)
Johann:
Migrate databases
We mentioned this in a slide before, but it’s very important that you do this. Look at the channels you use most, maybe it’s your website or your call centers. Ask yourself: have I integrated the data across various channels or consolidated it into one record?
Can I tell that John vs Jonathon are the same person?
What you can do about this is look at integrating matching and deduplicating solutions in your environment. If you have large datasets, think about a third-party solution to deduplicate those records for you. If you’re a smaller business, maybe a self-service solution is the smarter way to go. Our point is to look for solutions that are customizable to your environment.
Johann:
Accurate, complete addresses are critical to Saks’ renowned service. Every marketing objective they have like mail catalogs, special offers, or referencing specific preferences in conversations, is based on good data. They found out that a lot of bad addresses were entering their customer data warehouse from all their channels, and their employees were unknowingly creating duplicate records for the same customer. This was dramatically hurting their omnichannel marketing efforts.
They solved these problems by integrating a front-end address verification solution into their ecommerce website, call centers, and then web-based POS system. They now have standardized data coming into their databases, which not only makes it easier to consolidate and integrate data into their customer data warehouse, but their marketing efforts have also improved.
Johann:
Find out the percentage of inaccurate data in your database.
Johann:
That concludes our webinar, thanks for listening! I’d now like to open the floor to any questions you may have.