Riad Shalaby, CMO and Jeff Berke, CEO
When it comes to data-driven marketing, it’s all about propelling customer engagement. Simple as this idea may sound, putting it into practice is anything but easy.
To put things into perspective, let’s take the example of a consumer who is killing time using his mobile phone while in a waiting room, and he comes across an interesting product online. Later while retiring for the night, he suddenly remembers the product and sets off on exploring its features but this time using his tablet. The next day, he does further surveying of the product, but this time from the PC at his workplace. While the same consumer searches for the same product three times on different devices, behind the scenes, the brand treats those as three discrete prospects. This is where data-driven marketing goes for a toss, underlining the massive predicament that brands face: how to interact with a consumer across the channels and devices by focusing on the person behind those devices so the brand can be engaging and relevant at each interaction. “Clearly, there is an immense proliferation of data within the digital marketing ecosystem,” says Jeff Berke, the CEO of Audience Acuity, a firm that enables its clients to identify and separate their target audience from the masses. “This is why we have chosen to focus our efforts on the next evolution by developing broader-scale data products revolving around mobility and the Internet of Things (IoT) and the tidal wave of change that it will create. Through our methodology, we allow firms to interact with audiences in a contextual manner across all channels.”
It is the experience that Berke and his team have in the data-driven marketing landscape that steers Audience Acuity ahead of the competition curve. With 20 years of rich experience in guiding firms on the use of data, Berke’s propensity toward data comes as a natural progression for him to run Audience Acuity as the CEO and guide the firm’s development of next-generation data capabilities.
Focused on Customer Acquisition
Identity management and recognition across channels, and even devices for that matter is the key to managing customer journeys and measuring online and offline behavior. Consumer recognition through identity matching and validation has become the top priority for the marketing industry and ultimately enables businesses to personalize offers and campaigns, dynamically alter web content, and drive in-app marketing as part of managing the customer journey.
We have chosen to focus our efforts on the next evolution by developing broader-scale data products revolving around mobility and the Internet of Things (IoT)
Berke well perceives the practical details of customer data management in the dynamics and challenges of the data-driven marketing ecosystem. He adds, “Every major brand encounters significant complications when it comes to gaining precision in customer data accuracy at the scale of their customer population. Moreover, the migration of customers from one channel, or device, to another aggravates the complexity further.” Audience Acuity helps address these challenges by providing data, a platform, and execution services to facilitate customer acquisition marketing. Their platform has all the major digital consumer identifiers with which it compares favorably versus basic Identify Graphs (ID Graphs) that offer only one or perhaps a pair of unique identifiers used to identify a consumer.
In order to illustrate better, Berke sheds light on a study released last November by SiriusDecisions called “The Global CMO Study,” which speaks of the major barriers that CMOs identified in the shift to a customer-centric operation. First off, most organizations falter when it comes to the quality and the coverage of the customer data and matching offline datasets to online datasets which ultimately impairs engagement and conversion. The other issue is organizational expertise; companies are constantly on the lookout for marketing personnel competent in addressable advertising, leveraging social, digital, and e-mail in tandem for both active and non-authenticated customers. Precise data curated through a proprietary data science routine serves as the nucleus of the company, and as a result Audience Acuity is perfectly positioned to help overcome these hurdles with its primary focus on aggregating and providing datasets that facilitate audience development and targeting at scale. The company’s datasets include a Super Identity Graph, a National Consumer Database, and a Business Contact Database. Catering to identity management and cross-channel and -device recognition, Audience Acuity’s state-of-the-art Super Identity Graph provides an organized dataset containing core postal information on the U.S. adult population, deterministically paired to their digital identifiers including email, hashed email, mobile ad IDs, social handles, IPs, mobile phones and landline phones. The National Consumer Database contains the core postal information and over 500 data elements based on lifestyle, demographics, interest, and aggregated purchase history. This in-turn enables brands to fully understand a consumer so that they contextually interface with them. And both data products share common record IDs allowing the consumer insight and digital identifiers to be linked.
The Ultimate Data-Driven Approach
Berke states, “We have highly accurate offline data that is individually compiled and built on 100 percent deterministic matching, and this is our foundation.” Audience Acuity uses a thorough offline data hygiene process to standardize, normalize, cleanse, group, and analyze the data. Following that, the data is compared against truth sets, by two third-party validations to avoid all the false positives found in digital advertising. Utilizing the precise offline data and aggregated transaction data, the company then deterministically matches the consumers with their digital identifiers, such as e-mail address and phone number, while adhering to DMA privacy and security compliance policies.
"We have highly accurate offline data that is individually compiled and built on 100 percent deterministic matching, and this is our foundation"
Additionally, Audience Acuity’s analytical solution uses a stepwise linear regression to produce customer profiles that identify predictive traits of any dataset that might not be otherwise uncovered. “Clients typically use the report to aid audience targeting for acquiring new customers, identify predictive traits of a customer base, or define a specific behavior of a customer segment, which can then be used for data enhancement to improve segmentation,” informs Berke.
Extracting Maximum Marketing Value
Audience Acuity adheres to a customer-centric operating model that focuses on a client’s situation, their objectives, barriers they are facing, and the functionalities they need. Following that, they address the situation in two different ways: licensing and installing the ID graph or National Customer Database into the client’s data management platform (DMP) or by allowing clients to access Audience Acuity’s cloud-hosted data environment through the firm’s proprietary API library. Additionally, the company offers a services layer to help clients extract maximum value by activating their data. “At Audience Acuity, we enable clients to build an individual audience that meets their exact criteria and then provide them that audience data for offline use as well as onboarding the data as a custom audience for use across the digital ad ecosystem,” mentions Berke.
Founded in 2015 as an aggregator of marketing and referential data assets, Audience Acuity has come a long way to include mobile and digitally focused datasets that are both unique and highly authoritative. “We have substantial organizational bench strength in the data world and have assembled an advisory board of recognized thought leaders in data products and the use of such to drive business objectives,” says Berke. Forging ahead, Audience Acuity intends to continue creating a rich understanding of people across channels and devices and is looking to implement AI and machine learning to identify communication-based patterns quickly.